Lambropoulos Phd Thesis 08

TOOLS AND EVALUATION TECHNIQUES FOR

COLLABORATIVE E-LEARNING

COMMUNITIES

Niki Lambropoulos (Lampropoulou)

Submitted for Examination of Doctor of Philosophy

Center for Interactive Systems Engineering London South Bank University

London United Kingdom

Tools and Evaluation Techniques for Collaborative E-Learning Communities

To my friends, family

the Greek teachers

Ph.D. Thesis Centre for Interactive Systems Engineering LSBU ii

Is the sand other than the rocks? That is, is the sand perhaps nothing but a greater number of very tiny stones? Is the moon a greater rock? If we understood rocks, would we also understand the sand and the moon? Is the wind a sloshing of the air analogous to the sloshing motion of the water in the sea? What common features do different movements have? What is common to different kinds of sound? How many different colours are there? And so on. In this way we try gradually to analyse all things, to put together things which at first sight look different, with the hope that we may be able to reduce the number of different things and thereby understand them better. Richard P. Feynman, Six easy Pieces. 1995, p. 23-24.

Ph.D. Thesis Centre for Interactive Systems Engineering LSBU iii

Acknowledgments

First, I want to express my thanks to Xristine Faulkner and Fintan Culwin, my

Supervisors, for all they have done to support me in my studies. Both have given

generously of their time and talents, and it is my (possibly biased) view that they provide

a model of PhD supervising at its best. I cannot thank them enough. In addition, Louise

Campbell and Chung Lam from the Research Office for helping all research students at

LSBU on an individual basis.

Many other people have also provided valued input to my research through discussions,

participating in empirical work, or commenting on written work (or more than one of

these). I particularly wish to thank Sophi Danis, Sara BenIsaac, my Yoga mates,

especially Ilana Isserow, Jennifer Pearl and Lesley Todd, who have been through the

course with me; John Henderson for all the fun and support; also Catherine Spiro, Betty

Shane, Ben Daniel, Martha Christopoulou and last but not least, Mariza Smirli for their

help and support.

Special thanks to my Dad, Konstantinos, my Mum, Aphrodite and my Sister, Georgia for

being such a tolerant and supportive family.

Most of my work has been funded by the Greek Ministry of Education and Religious

Affairs given as three years of educational paid leave of absence. For this, I need to

thank Theodoros Birbas, Socratis Papathanasiou, Epaminondas Georgopoulos, and

Panayiotis Zevlas. In addition, many thanks to the Greek School Network and in

particular, Michael Paraskevas and Vangelis Grigoropoulos for their help and providing

access to research space.

I need to thank my mates in the Dream-e-Team, Marianna Vivitsou, Dimitris Konetas,

Alexander Gkikas, Sofia Papadimitriou, Panayiotis Kampylis, Elias Economakos, and

especially Nikos Minaoglou, for the unimaginable creative collaboration all these years.

Great thanks to Alexander Muir, Jenny Preece and Ben Shneiderman for the continuous

inspiration as well as their insights and energy that enabled me to overcome obstacles.

Finally, special thanks to my examiners, Dr Judy Ramsay and Professor Stephen Lerman

for the detailed comments and insights that improved this thesis.

Ph.D. Thesis Centre for Interactive Systems Engineering LSBU iv

Declaration

I grant powers of discretion to the University Librarian to allow this thesis to

be copied in whole or in part without further reference to me. This permission covers

only single copies made for study purposes, subject to normal conditions of

acknowledgment.

Ph.D. Thesis Centre for Interactive Systems Engineering LSBU v

Abstract

This study provides new multidisciplinary approaches for tools and evaluation

techniques to ensure quality in collaborative e-learning communities. The research

problem was the Greek teachers’ absence of participation in e-learning discussions

for 3 years. Three conceptual frameworks were used to understand and evaluate the

situation: passive and active participation, the collaborative e-learning episode, and

the sense of e-learning community index. Two interventions were made, collaborative

e-learning and the introduction of associated software-based tools: participation

graphs and avatars, MessageTag, a tool to depict the levels of critical thinking in

collaborative e-learning, and social network analysis tools, the visualisation

interactions nodes and centrality. Ethnotechnology was the research design

triangulating quantitative and qualitative data as well as social network analysis.

The originality of this study lies in the investigation of the processes on the social and

learning aspects of collaborative e-learning and associated tools.

The results indicated that the suggested frameworks and tools can be useful in

supporting collaborative e-learning communities.

The wider implications from the findings emphasise the need for: the organisations’

e-learning readiness; the e-learners’ prior knowledge and ability to interact; the

facilitation of e-learners’ social awareness; the change of teaching and learning

approaches for different levels and types of interactions, participation, and critical

thinking; the development of collaborative e-learning communities; the use of tools

anchored in learner-centred design and solid pedagogical frameworks. If all

components are present in an online course then e-learning quality can be ensured.

Ph.D. Thesis Centre for Interactive Systems Engineering LSBU vi

Περίληψη

Αυτή η έρευνα έχει βασιστεί σε διεπιστημονικές προσεγγίσεις για εργαλεία και

τεχνικές αξιολόγησης με σκοπό να εξασφαλίσει την ποιότητα στις συνεργατικές

διαδικτυακές μαθησιακές κοινότητες. Το ερευνητικό πρόβλημα στηρίχτηκε στην

απουσία συμετοχής των Ελλήνων εκπαιδευτικών σε συζητήσεις διαδικτυακών

μαθημάτων για 3 χρόνια. Τρία εννοιολογικά πλαίσια χρησιμοποιήθηκαν για να

κατανοηθεί και να αξιολογηθεί η περίπτωση: παθητική και ενεργητική συμμετοχή, το

επεισόδιο συνεργατικής μάθησης, και ο δείκτης αισθήματος ‘ανήκειν’ στη διαδικτυακή

μαθησιακή κοινότητα. Έγιναν δυο παρεμβάσεις, η συνεργατική μάθηση και η

εισαγωγή σχετικών εφαρμογών: αυτά είναι γραφήματα και άβαταρ συμμετοχής, το

εργαλείο MessageTag για την αναπαράσταση των επιπέδων κριτικής σκέψης στη

συνεργατική διαδικτυακή μάθηση, και τα εργαλεία ανάλυσης κοινωνικών δικτύων για

την απεικόνηση των διαδράσεων με βάση τους διαδραστικούς κόμβους και την

κεντρικότητα. Η ερευνητική μεθοδολογία ήταν η Εθνοτεχνολογία και

χρησιμοποιήθηκε για το συνδυασμό ποσοτικής και ποιοτικής ανάλυσης και ανάλυσης

κοινωνικών δικτύων με σκοπό την εγκυρότητα των αποτελεσμάτων.

Η πρωτοτυπία αυτής της έρευνας έγκειται στην ερευνητική διαδικασία για την

κοινωνική και μαθησιακή διάσταση της συνεργατικής μάθησης και των σχετικών

εργαλείων. Τα αποτελέσματα έδειξαν ότι τα προτεινόμενα πλαίσια και εργαλεία

μπορεί να είναι χρήσιμα για την υποστήριξη των διαδικτυακών μαθησιακών

κοινοτήτων.

Οι ευρύτερες επιπτώσεις από τα αποτελέσματα δείχνουν την ανάγκη για: την

ετοιμότητα των οργανισμών όσον αφορά τη διαδικτυακή εκπαίδευση, την

προηγούμενη γνώση και ικανότητα των εκπαιδευομένων για διάδραση, τη

διευκόλυνσή τους για κοινωνική συνειδητοποίηση, την αλλαγή που έχει υπάρξει στις

μεθόδους διδασκαλίας και μάθησης για διαφορετικά επίπεδα και τύπους διάδρασης,

συμμετοχής και κριτικής σκέψης, την ανάπτυξη διαδικτυακών μαθησιακών

κοινοτήτων, και τέλος τη χρήση εργαλείων βασισμένων στο χρηστο-κεντρικό

σχεδιασμό και ισχυρές παιδαγωγικές προσεγγίσεις. Εάν όλα τα στοιχεία είναι

υπαρκτά σε ένα διαδικτυακό μάθημα τότε η ποιότητα της διαδικτυακής εκπαίδευσης

μπορεί να εγγυηθεί.

Ph.D. Thesis Centre for Interactive Systems Engineering LSBU vii

Table of Contents Acknowledgments …………………………………………………………… iv Declaration ……………………………………………………………………. v Abstract ……………………………………………………………………….. vi Περίληψη (Abstract in Greek) ……………………………………………… vii Table of Contents …………………………………………………………… viii Index of Tables ……………………………………………………………… xi Index of Figures …………………………………………………………….. xiii Index of Graphs …………………………………………………………….. xiv Index of Appendices ……………………………………………………….. xv Chapter 1: Introduction ……………………………………………………. 1

1.1 INTRODUCTION ………………………………………………………….. 2 1.2. EDUCATORS’ ONLINE TRAINING ………………………………….... 3

1.2.1 Greek teachers’ online training ……………………………… 5 1.3. QUALITY IN ONLINE EDUCATION …………………………………… 7 1.4. AIMS AND RESEARCH QUESTIONS ………………………………… 9 1.5. OVERVIEW OF THE CHAPTERS …………………………………….. 11 REFERENCES …………………………………………………………………. 12

Chapter 2: The Literature Review ……………………………………… 14

2.1 INTRODUCTION ……………………………………………………….. 15 2.2. COLLABORATIVE LEARNING ……………………………………... 15

2.2.1 From the Individual to the Community: a Brief History … 18 2.3 ONLINE & E-LEARNING COMMUNITIES …………………………… 24

2.3.1. Passive Participation in Online Communities …......... 25 2.3.2 Passive Participation in e-Learning Communities ….. 27

2.4 DESIGN FOR LEARNERS AS USERS & USERS AS LEARNERS .. 31 2.4.1 Socio-Technical & User-Centred Design …………………. 31

2.4.1.1 Towards a Learner-Centred Design ……………. … 33 2.4.2 Instructional Design & Engineering ………………………... 34

2.5. TOOLS FOR COLLABORATIVE E-LEARNING COMMUNITIES ... 38 2.5.1. When the Online Community Met E-Learning ………... 41

2.5.1.1. Design Principles for e-Learning Communities …... 42 2.5.1.2. E-Learning Tools & Interface Design …………....... 44

2.5.2. Tools to Support Collaborative e-Learning Communities ……………………………………………. 45

2.5.2.1. Tools to Structure Dialogical Sequences ……....... 46 2.6 PROPOSITIONS FOR DESIGN ………………………………………. 51

2.6.1. Collaborative e-Learning Episodes …………………… 51 2.6.2. Levels of Participation ………………………………….. 53 2.6.3. The Sense of e-Learning Community Index …………. 55

REFERENCES ………………………………………………………………… 56

Ph.D. Thesis Centre for Interactive Systems Engineering LSBU viii

Chapter 3: The Research Design ………………………………………. 67 3.1 INTRODUCTION ……………………………………………………….. 68

3.1.1. E-Learning Research ………………………………………… 68 3.2 RESEARCH DESIGN ……………………………………………………. 70

3.2.1. Examining the Research Context ……………………………. 70 3.2.1.1 Ethnography …………………………………..………. 71 3.2.1.2 Ethnotechnology: the virtual ethnography …............. 72 3.2.1.3 Ethnotechnological methods …………………………. 73

3.2.2. In the Search for Quality: Human-Human Interaction Analysis …………………………………………………….. 76

3.2.2.1 Posts: Thematic analysis ……………………………… 76 3.2.2.2 Interactions: Social network analysis ………………… 79

3.2.3. Questionnaire Design ………………………………………….. 81 3.2.4. E-Research Coordination: Time-short series design ………… 83 3.2.5. Research Constraints ………………………………………….. 86

REFERENCES ………………………………………………………………….. 87

Chapter 4: The Research Context ………………………………………. 92 4.1 INTRODUCTION ………………………………………………………… 93

4.1.1. The Native’s Point of View: background and Characteristics ……………………………………………. 93

4.2 IDENTIFYING INTENTIONS …………………………………………… 96 4.3 PLANNING ………………………………………………………………. 99

4.3.1. Moodle@GSN: Moodle at the Greek School Network .. …. 99 4.3.1.1 Users and activity at Moodle@GSN ……………. 100

REFERENCES ………………………………………………………………… 107 Chapter 5: Tools & Evaluation Techniques ……………………….. 108

5.1 INTRODUCTION ………………………………………………………... 109 5.2 COLLABORATIVE E-LEARNING TOOLS …………………………… 110

5.2.1. Design for initial design: Create prototype for testing by the e-learners …………………………………… 110 5.2.1.1. Presence & Co-Presence Awareness:

Visualisations Interactions Tools ………………… 111 5.2.1.2. Participation Awareness:

Evaluation Participation Tools …………………… 112 5.2.1.3. Structuring Collaborative E-Learning:

MessageTag ……………………………………… 113 5.2.2. The E-mmersion Block ……………………………………… 115

5.2.2.1. Tools Evaluation Pool ………………………………. 118 5.2.2.2. Application of guidelines and heuristics from

feedback in design …………………………….. 125 5.2.2.3. Implications for Research design ………………… 127

5.2.3. Greek teachers Moodle developers ………………………. 130 5.2.3.1. Application of guidelines and heuristics from

feedback in design …………………………….. 133 REFERENCES ………………………………………………………………… 136

Ph.D. Thesis Centre for Interactive Systems Engineering LSBU ix

Chapter 6: Main Study …………………………………………………. 137 6.1 INTRODUCTION ……………………………………………………….. 138

6.1.1. Initial activities ……………………………………………….. 139 6.2 DESCRIPTION OF THE RESEARCH CONTEXT ………………….. 141

6.2.1. Who are the Greek teachers? ……………………………… 141 6.2.2. Conditions of working and learning online ………………… 142 6.2.3. Previous Knowledge of collaborative e-learning techniques & participation ……………………………………………. ….. 144

6.3 TRACING PARTICIPATION …………………………………………… 147 6.3.1. Frequency of visits …………………………………………… 147 6.3.2. On Participation ………………………………………………. 151

6.3.2.1. Active and passive participants ……………………. 151 6.3.2.2. Active participation levels …………………………… 152 6.3.2.3. Passive participation levels …………………………. 153

6.4 THE COLLABORATIVE E-LEARNING EPISODES ………………… 158 6.4.1. Quantitative variables …………………………………….. … 158 6.4.2. Qualitative variables …………………………………………. 160

6.5 THE SENSE OF THE E-LEARNING COMMUNITY INDEX ……….. 166 6.5.1. Community evolution ………………………………………… 167 6.5.2. Sense of belonging ……………………………………….. … 172 6.5.3. Empathy ………………………………………………………. 174 6.5.4. Trust …………………………………………………………… 177 6.5.5. Intensity ……………………………………………………….. 178 6.5.6. E-learning quality …………………………………………….. 182 6.5.7. Global Social Network Analysis …………………………….. 184

6.5.7.1. Global cohesion ……………………………………… 186 6.5.7.2. Global centrality ……………………………………… 192 6.5.7.3. Local nodes and centrality in real time ……………. 197

6.6 PEDAGOGICAL USABILITY ....................………………………….... 201 6.6.1. Pedagogical Usability ............................…………………… 201 6.6.2. Correlations & crosstabulations ……………………………… 204

6.7 INTERVENTION ANALYSIS ………………………………………...... 209 REFERENCES ………………………………………………………………… 215

Chapter 7: Conclusions………………………………………………... 218

7.1 INTRODUCTION ………………………………………………………… 219 7.2 SCOPE OF FINDINGS …………………….…………………………… 219 7.3 CONTRIBUTIONS ………………………………………………………. 222

7.3.1. Key contributions …………………………………………….. 222 7.3.2. Secondary contributions …………………………………….. 223

7.4 THESIS LIMITATIONS ………………………………………………… 225 7.5 CONCLUSIONS ………………………………………………………… 225 REFERENCE .…………………………………………………………………. 232

Appendices ……………………………………………………………………… 234 Glossary …………………………………………………………………………… 285

Ph.D. Thesis Centre for Interactive Systems Engineering LSBU x

Index of Tables Chapter 1 Table 1.5-1. Chapters Overview ……………………………………………………… 11 Chapter 2 Table 2.2.1-1. The Socially-Shared Cognition Approach ………………………….. 21 Table 2.3.2-1. Reasons for lurking in e-learning communities ................................ 29 Table 2.3.2-2. Strategies for enhancing activity in e-learning .................................. 29 Table 2.4.2-1. Instructional Design problems …………………………………………. 36 Table2.5.1.1-1. Design principles for online and e-learning communities ................ 42 Table 2.5.2.1-1. Learning and Instructional Activities ……………………………….. 46 Table 2.5.2.1-2. MessageForum Collaborative Learning Attributes ………………… 48 Table 2.5.2.1-3. Similarities and differences between MessageForum & InterLock 50 Table 2.6.2-1. Levels of participation measurement …………………………………. 53 Table 2.6.2-2. Levels of activity measurement ………………………………………... 54 Chapter 3 Table 3.2-1. Research Design ………………………………………………………….. 70 Table 3.2.2.1-1. Collaborative e-Learning Episodes Coding Matrix ………………… 78 Table 3.2.4-1. Observations, interventions and evaluation ………………………… 84 Table 3.2.4-2. Limitations and strengths in Time-Short Series …………………….. 84 Table 3.2.4-1. Research methodology ……………………………............................ 85 Chapter 4 Table 4.3.1.1-1. Courses categories and number of e-learners ………………… 100 Table 4.3.1.1-2. e-Learners’ posts and views in the 6 active courses …………….. 103 Table 4.3.1.1-3. e-Learners’ replies and dates ………………………………………. 104 Table 4.3.1.1-4. E-Learning Engineering for Moodle@GSN ……………………….. 106 Chapter 5 Table 5.2.-1. Iterative Design Blocks ………………………………………………… 110 Table 5.2.2.1-1. Use of MessageTag …………………………………………………. 123 Table 5.2.2.3-1. Research Design …………………………………………………… 129 Table 5.2.3-1. Demographics for the three Greek Teachers / Moodle Developers 130 Table 5.2.3-2. Questionnaire open questions …………………………………….…. 131 Table 5.2.3-3. Tools Pedagogical Usability Scores …………………………………. 132 Chapter 6 Table 6.1.1-1. The questionnaires’ selection process ……………………………… 139 Table 6.2.3-1. Greek teachers’ knowledge and attitudes on collaboration and participation ……………………………………………………… 145 Table 6.3.1-1. Moodle@GSN forums and users view log files ………………….. 147 Table 6.3.1-2. Forums and users view log files in the research pool …………… 148 Table 6.3.1-3. Total number of posts ……………………………………………… 148 Table 6.3.1-4. Temporal overview of all activities ………………………………… 149 Table 6.3.1-5. Temporal overview of posted messages (add post/forum) …….. 150 Table 6.3.2.1-1. Number of active and passive participants …………………….. 151 Table 6.3.2.2-1. Active participation levels (Initial proposition) ………………….. 152 Table 6.3.2.2-2. Active participation levels (Second proposition) ………………. 153 Table 6.3.2.3-1. Passive Participation Levels …………………………………….. 154

Ph.D. Thesis Centre for Interactive Systems Engineering LSBU xi

Table 6.3.2.3-2. Posts from passive participants ………………………………… 155 Table 6.4.2-1: Collaborative E-Learning Episodes Overview ………………….. 160 Table 6.4.2-2. Collaborative e-Learning Episodes selected for analysis ……… 161 Table 6.4.2-3. Collaborative e-Learning Episodes temporal overview ………… 162 Table 6.4.2-4. CeLEs: e-learners and e-tutors’ contributions ………………….. 163 Table 6.5.1-1. Knowing the community …………………………………………… 169 Table 6.5.3-1. Empathy factors ……………………………………………………. 174 Table 6.5.3-2. Correlations for Empathy factors …………………………………. 176 Table 6.5.4-1. Trust levels …………………………………………………………… 177 Table 6.5.4-2. Trust development towards individuals ………………………….. 177 Table 6.5.5-2. Persistence in Moodle@GSN …………………………………….. 179 Table 6.5.5-3. Persistence in the research pool …………………………………. 181 Table 6.5.7.1-1. Group Network Cohesion: Density & Reciprocity …………….. 186 Table 6.5.7.1-2. Cliques …………………………………………………………….. 188 Table 6.5.7.1-3. Cliques in Structural Equivalence ………………………………. 192 Table 6.5.7.2-1. Group Centrality …………………………………………………… 193 Table 6.5.7.2-2. Top 10 Scorers in Out-Degree Centrality ………………………. 194 Table 6.5.7.2-3. Top 10 Scorers in In-Degree Centrality ………………………… 195 Table 6.6.1-1. Overall scores for the collaborative tools’ usability and utility ….. 201 Table 6.6.1-2. Use of MessageTag in the Research pool ……………………….. 202 Table 6.6.2-1. Time using LMS * Frequency of Use ……………………………… 206 Table 6.6.2-2. Training on LMS * Frequency of Use ……………………………… 207 Table 6.7-1. Intervention Analysis ………………………………………………….. 209 Table 6.7-2. E-learning engineering ……………………………………………….. 210 Table 6.7-3. The Sense of e-Learning Community Index Checklist ……………. 212

Ph.D. Thesis Centre for Interactive Systems Engineering LSBU xii

Index of Figures Chapter 2 Figure 2.2.1-1 The Eyeball of Participation ………………………………………… 22 Figure 2.5-1. Google trend history for online community and e-learning …………. 39 Figure 2.5-2. PLATO III ………………………………………………………………… 40 Figure 2.5.2-1: Categorisation of collaborative learning tools ................................. 45 Figure 2.5.2.1-1. InterLock Interface ………………………………………………..…. 47 Figure 2.5.2.1-2. MessageForum Attributes in a Discussion Topic ………………… 49 Figure 2.6.1-1. The Collaborative E-learning Episode (CeLE) ……………………….52 Figure 2.6.2-1. Participation Levels in Collaborative e-Learning Communities …… 54 Chapter 3 Figure 3.2.1.3-1 Ethnotechnology and methods ……………………………………... 75 Figure 3.2.3-1. Questionnaire Design Methodology ………………………………… 82 Chapter 4 Figure 4.2-1. Organisation of the Education System in Greece 2003/04 …………. 96 Figure 4.3.1-1. Moodle@GSN research context …………………………………….. 99 Chapter 5 Figure 5.2.1.1-1. Visualisation Interaction Tools (VIT) Nodes & Centrality …........ 111 Figure 5.2.1.1-2. Visualisation Interactions Tools (VIT) production line ………….. 111 Figure 5.2.1.2-1. Course and individual participation levels graph ………………. 112 Figure 5.2.1.2-2. Participation evaluation graphs production line …………………. 113 Figure 5.2.1.2-1. Initial Design for Message Tagging ………………………………. 114 Figure 5.2.2-1 Total Codes Network in the Web Design pool ............................ 117 Figure 5.2.2.1-1. Participants and number of messages (ATLAS.ti) ……………… 118 Figure 5.2.2.1-2. Location of VIT on the discussion forum …………………………. 119 Figure 5.2.2.1-3. VIT Nodes …………………………………………………………… 119 Figure 5.2.2.1-4. VIT Centrality ………………………………………………………... 119 Figure 5.2.2.1-5. MessageTag …………………………………………………………. 122 Figure 5.2.2.2-1. Lurkers overall view in VIT Centrality (right) ……………………. 124 Figure 5.2.2.2-2. Redesign of participation graphs …………………………………. 126 Figure 5.2.2.2-3 CeLE MessageTag tool ……………………………………………… 127 Figure 5.2.3.1-1. Discussion on tools’ Greek names ……………………………….. 134 Figure 5.2.3.1-2. Pedagogical Usability Attributes ................................................ 135 Chapter 6 Figure 6.1.1-1. The e-tutors in the online course ……………………………………. 138 Figure 6.1.1-2. Normality overview for tools pedagogical usability and utility

in HCE ……………………………………………………………….. 140 Figure 6.2.1-1. Participants’ location in Greece …………………………………… 142 Figure 6.5.7-1. GSN adjacency matrix in UCINET ……………………………….. 185 Figure 6.6.2-1. Correlations analysis in HCE 3.0 ………………………………… 204

Ph.D. Thesis Centre for Interactive Systems Engineering LSBU xiii

Index of Graphs Chapter 4 Graph 4.3.1.1-1. Online course categories in Moodle@GSN ……………………… 101 Graph 4.3.1.1-2. Comparison between number of messages and replies ............. 102 Graph 4.3.1.1-3. Activity in the online course …….…………………………………. 104

Chapter 5 Graph 5.2.2-1. Participating countries ……………………………………………….. 115 Graph 5.2.2.1-1. 31/03/2006 – 5/28 e-learners ……………………………………… 121 Graph 5.2.2.1-2. 04/04/2006 – 10/28 e-learners …………………………………….. 121 Graph 5.2.2.1-3. 08/04/2006 – 10/28 e-learners …………………………………….. 121

Chapter 6 Graph 6.2.2-1. Correlations between time in education, use of computers, and Learning Management Systems (LMS) …………………….. 143 Graph 6.2.3-1. Communication with the educational authorities …………………. 146 Graph 6.3.1-1. Comparison between sent messages and

messages for analysis ................................................................. 149 Graph 6.3.1-2. Logs of overall activity VS posting ………………………………… 150 Graph 6.3.2.3-1. Active & Passive Participation locus

from the same participants ....................................................... 155 Graph 6.4.1-1. Comparison between messages for analysis, richness of text, And discussion depth ……………………………………………. 159 Graph 6.4.2-1. CeLEs factors’ comparison graph …………………………………. 162 Graph 6.4.2-2. Comparison for number of words posted by e-learners and e-tutors ……………………………………………………….. 164 Graph 6.5.1-1. Community evolution elements ……………………………………. 167 Graph 6.5.1-2. New members’ contributions ………………………………………… 170 Graph 6.5.1-3. Roles in the e-learning community ……………………………….. 172 Graph 6.5.2-1. Participants’ opinions on e-learning community elements …….. 173 Graph 6.5.2-2. Comparison of themes and community elements ………………. 174 Graph 6.5.3-1. Scatter plot for empathy …………………………………………… 175 Graph 6.5.5-1. Passive & Active Participation Process …………………………. 178 Graph 6.5.6-1. Elements that show community evolution: e-learning …………. 182 Graph 6.5.6-3. The e-learning facilitators …………………………………………. 183 Graph 6.5.6-2. Correlations between codes on collaborative e-learning quality 184 Graph 6.5.7.1-1. Reciprocal ties in GSN (a) & the research pool (b) ………….. 187 Graph 6.5.7.1-2. Structural equivalence dendrogrammes in GSN (all) ……….. 170 Graph 6.5.7.1-3. Structural equivalence dendrogrammes in the

research pool (all) …………………………………………… 170 Graph 6.5.7.1-4. Structural equivalence dendrogramme in GSN (e-learners) .. 191 Graph 6.5.7.1-5. Structural equivalence dendrogramme in the

research pool (e-learners) ………………………………… 191 Graph 6.5.7.3-1: VIT Nodes in CeLE IX ………………………………………….. 198 Graph 6.5.7.3-2. VIT Centrality in CeLE IX ………………………………………. 199

Ph.D. Thesis Centre for Interactive Systems Engineering LSBU xiv

Index of Appendixes

Appendix I: Online Community Management …………………………………… 234 A_I_1. Moderator’s Responsibilities - Interactivity Management ........ 234 A_I_2. Suggestions for Writing Online Messages ............................... 235 Appendix II: Risk Management …………………………………………………… 236 Appendix III: Initial Questionnaire (sample) ……………………………………. 239 A_III_1. The usability section in the Initial Questionnaire ................... 239 Appendix IV: Questionnaire Main study I (sample) ……………………………... 240 A_IV_1. Demographic data .................................................................... 240 Appendix V: Questionnaire Main study II ………………………………………... 242 Appendix VI: Participants’ Documents ……………………………………………. 250 A_VI_1. Invitation to the study ................................................................ 250

A_VI_2. Netiquette ................................................................................. 250 A_VI_3. Instructions of use Moodle and the Research Pool ............... 251

Appendix VII: The E-mmersion Data Analysis …………………………………….. 252 A_VII_1. Demographics ........................................................................... 252 A_VII_2. Crosstabulation: Internet Use in class *

Use for educational purposes ......................................... 253 A_VII_3. Crosstabulation: Moodle Use * Time using LMS ..................... 253 A_VII_4. Moodle Usability ....................................................................... 253

A_VII_5. Training in Educational Technologies .................................... 253 A_VII_6. Reasons for participating in e-learning communities ............ 254 A_VII_7. Use of e-learning tools .............................................................. 254 A_VII_8. Messages Quantitative Analysis ............................................... 254 A_VII_9. Forums and users view log files ............................................... 255 A_VII_10. Participation in e-learning Communities ............................... 255 A_VII_11. Online course experience ...................................................... 256 A_VII_12. Messages Analysis: Collaborative E-Learning Episode I ... 257 A_VII_13. CeLE 1 (AIa-1:stanzas1-25) .................................................. 258 A_VII_14. Participant SP1: Thought Processes ..................................... 262

Appendix VIII: Conditions of working and learning online ……………………. 263 Appendix IX: Thematic Analysis in the Main Study ……………………………… 264 A_IX_1. Post-retreat opinions on participation ..................................... 264

A_IX_2. Post-retreat opinions on e-learners’ participation in the project .................................................................... 264

A_IX_3. Post-retreat opinions on new members’ contribution ............ 265 A_IX_4. Post-retreat opinions on communities ..................................... 266 A_IX_5. Post-retreat opinions on other communities ........................... 266 A_IX_6. Post-retreat opinions on new members’ contribution ............ 267 A_IX_7. Post-retreat opinions on learning ........................................... 267

Appendix X: Collaborative e-Learning Episodes (Examples from the Main Study ……….. ………………………………………………. 268 A_X_1. Collaborative e-Learning Episode III .......................................... 268 A_X_2. CeLE-III Locus (CeLE-CIII: Stanzas 4-23) .................................. 269 A_X_3. CeLE-III Analysis ........................................................................ 270 A_X_4. CeLE-III Code Network ............................................................... 270 A_X_5. Internalisation and externalisation thought process ............... 271 A_X_6. Collaborative e-Learning Episode IX ......................................... 271

Ph.D. Thesis Centre for Interactive Systems Engineering LSBU xv

Ph.D. Thesis Centre for Interactive Systems Engineering LSBU xvi

A_X_7. Internalisation and externalisation thought process ................. 276 A_X_8. CeLE-IX Locus (CeLE-GIX: Stanzas 2-84) .................................. 276 A_X_9. CeLE-IX Analysis .......................................................................... 277 A_X_10. CeLE-IX Code Network .............................................................. 278

Appendix XI: Messages Quantitative Analysis …………………………………….. 280 A_XI_1. Messages Quantitative Analysis in Moodle@GSN .................. 280 A_XI_2. Messages Quantitative Analysis in the Research Pool .......... 281

Appendix XII: Main Study Data & Reports …………………………………………. 282 A_XII_1. Pedagogical Usability – Utility results ………………………… 282

A_XII_2. Correlations in SPSS …………… ……………………………… 285 A_XII_3. Most important correlations in the

Hierarchical Clustering Explorer ….................................…....... 286 A_XII_4. The best thing in the project ……………………………………… 288 Appendix XIII: Recommendations ………………………………………………….. 289

Tools and Evaluation Techniques for Collaborative E-Learning Communities Chapter 1: Introduction

Ph.D. Thesis Centre for Interactive Systems Engineering LSBU Page 1

Introduction: The problem of e-learning quality related to socio-cultural

learning and participation in e-learning communities

Key Topics Covered in This Chapter:

• What the study is about

• Why educators’ online training is important for their professional development

• The problem of quality in online education as a distinction between provision of information and acquisition of knowledge

• Aims and research questions

• Overall structure of the thesis

Chapter 1 introduces the research context, the research problem and the aims and

objectives of this study. Because socio-cultural learning theories and e-learning

design techniques evolved separately, they lack convergence. This is one of the

causes of quality problems in e-learning. An example is presented from the Greek

teachers’ e-learning community project aimed at their professional training and

development. An initial study showed that the mere provision of information did not

facilitate new-knowledge construction. Consequently, this study targets the

development of evaluation techniques and associated tools to enhance participation

in collaborative e-learning communities.

1.1 INTRODUCTION

For the past 50 years two main trends have been observed in education, the

socio-cultural focus and the use of technology. However, these two trends have

evolved almost separately. Socio-technical design and user-centred design were

planning approaches aiming to acknowledge that the development of interactive

technologies increasingly relies on an appreciation of the social circumstances in

which systems are used. Educational or instructional design is the systematic

processing of activities to solve an instructional problem with the aid of technologies.

Nonetheless, educational design and in particular e-learning design neglected the

dual and situated persona of the learner; she acts as both a user and a learner. In

addition, the e-learning systems were found to be information-based mainly

supporting monologue instead of being communication-based towards dialogue. For

this reason they fail to support e-learners’ transition between internalisation to

externalisation and becoming active participants. Thus, mere provision of information

points to poor e-learning quality. So, if educational design could understand the

technology of collaborative practice, e-learning quality could be improved.

This chapter introduces the concept of quality in e-learning and examines its

relationship to socio-cultural collaborative learning and associated design. The

research context is the Greek teachers’ e-learning community, started in 2003 as part

of a project for online teachers’ training and aimed at enabling teachers to acquire

new competencies. However, these aims were not met because of passive

participation and this implies that information acquisition may not be automatically

related to collaborative learning. It appears that learning within e-learning

communities is not always successful.

1.2 EDUCATORS’ ONLINE TRAINING

Education is generally acknowledged as one of the crucial components of

personal and professional development. The integration of Information and

Communication Technology (ICT) in education as well as the social and collaborative

nature of the Internet provided another medium for communication and training;

however, despite the advantages, the problem of e-learning quality is evident

worldwide.

In his foreword for the United Nations Educational, Scientific and Cultural

Organization (UNESCO) report (2002), Daniels said that within a short time ICT has

become one of the basic building blocks of the modern society. Furthermore, the

current shift occurring in the Web from a static content environment where end users

are the recipients of information—defined as Web 1.0—to one where they are active

content creators—defined as Web 2.0—can be described as a transition to a more

distributed, participatory, and collaborative environment (Delich, 2006). Web 2.0 is a

platform where “knowledge-working is no longer thought of as the gathering and

accumulation of facts, but rather, the riding of waves in a dynamic environment”

(Downes, 2005). To Berners-Lee (2007), the Web is not only a technological tool but

also a social phenomenon that enables collaboration and creativity.

ICT is the backbone of the knowledge economy and has been recognised as an

effective tool for promoting economic growth and development (World Bank Report,

Chen & Kee, 2005). Despite the expansion of ICT, general access to ICT varies

across continents, and countries even within the same continent, indicating a digital

divide (Reddy & Manjulika, 2002). Organisations, educational institutions and

business have been investing in the use of ICT in Education, or in what ESRC now

calls Technology Enhanced Learning (TEL) (ESRC, 2006). E-Learning is a

component of TEL and describes learning via the Internet, intranet, and extranet (WR

Hambrecht and Co, 2000:8). The freedom that e-learning offers and the increasing

number of online courses provided by educational organisations offer new

opportunities for personal and professional development in a life-long learning

course. Nevertheless, teachers’ education has been severely criticized on the

grounds of both quantity and quality (e.g. Perraton & Potashnik, 1997; Darling-

Hammond & Bransford, 2005; Thompson & Schmidt, 2007).

To solve this problem, UNESCO suggests that countries need to keep pace with

technological development and the changing competencies, reflected in the

curriculum and teacher training. Economic advantage will accrue to a population that

acquires competencies in processing information into knowledge and applying it in

work and everyday life. These competencies are not only related to using the devices

but also working on procedures that give access to information and skilfully

transforming information into knowledge. As this is the task of the educator,

educational systems will become a national resource as important as the traditional

factors of production-land, labour, and capital. This in turn would cause educators to

become more important, their productivity and their wages should increase, but they

can also expect the nature of their jobs to change with a great deal of specialization

(UNESCO, 2002:633-640). To support this life-long learning context, companies and

institutions often use commercial Learning Management Systems (LMS) for online

teachers’ training. Commercial LMS like Centra, and Blackboard, and Open Source

software as Bodington, Dokeos or Moodle are nowadays widely used; for example,

there are more than 26,124 registered sites from 182 countries, 1,855 in the U.K.

(http://moodle.org/sites/, last access 29/05/2007), and 97 in Greece, one of them is in

the service provided by the Greek School Network (GSN).

However, e-learning international and national projects, such as UK eUniversity,

Universitas 21, or Global University Alliance, have not succeeded in meeting a

number of promises (Garrett, 2004; Oliver, 2005). Research studies have

demonstrated that e-learning has both positive and negative impacts in terms of

effectiveness and achievement of outcomes (Franklin et al., 2001; Sims et al., 2003).

One of the reasons is because e-learning has created confusion between the mere

supply of information and knowledge-building (Barbera, 2004; Whatley, 2004).

A number of projects have addressed teachers’ online training using LMS

successfully, for example, the international project ‘Tapped In’ on a voluntary basis

(Schlager & Fusco, 2004), the Australian National Quality Schooling Framework

(NQSF) (Hartnell-Young, et al, 2006), or the European projects ‘Implementing

Standards for European e-Tutor Training’ (on going, 2006-20071) and ‘E-Learning

Fundamentals’ (started in May 20072). However, not all projects were successful; an

example that failed to engage teachers in an e-learning community is the European

Minerva Project ‘Star Science’ aimed at collaboration between science teachers from

Ireland, UK, and Bulgaria (Harvey, 2003). According to Harvey, the UK failed to

1 Leonardo DaVinci project ‘Implementing Standards for European e-Tutor Training’ (ISEeTT, http://www.etutorportal.net/). ISEeTT aims to define the core curriculum and quality standards for European e-Tutor training in relation to different national contexts. The Greek partner is the Educational Research and Evaluation Group, Foundation for Research Technology - Hellas (http://www.forth.gr/). 2 There was no additional information for this project other than the website: http://fecone.passionforlearning.eu/.

participate and Bulgaria’s participation was minimal. Similarly, there was no

significant evidence of socio-cultural learning in the European project ‘E-learning

Fundamentals’ in which I took part in June of 2007.

In short, e-learning outcomes seem to be unpredictable.

1.2.1 Greek Teachers’ Online Training

In Greece, teachers’ training is mainly onsite and organised by the Greek

Pedagogical Institute in collaboration with the Greek Ministry of Education and

Religious Affairs. There were efforts to facilitate online teacher training either from

universities or governmental organisations in collaboration with Higher Education

Institutes. This means that isolated courses were developed as part of PhD studies,

for example at the University of the Aegean (Hlapanis & Dimitrakopoulou, 2005) or

projects based on collaborative activities between the Greek Pedagogical Institute,

the Research Academic Computer Technology Institute, and other Greek

universities. One of these initiatives is the use of Moodle as part of the Greek School

Network (GSN) services; Moodle@GSN was built to aid Greek teachers’ online

training by developing an online community. (There is no agreement between

researchers on a single definition of community. In this study, a community is “a

group of people who consciously share a sense of belonging anchored in common

interests and enhanced by social interactions”. An online community is a community

where social interactions are facilitated by information and communication

technologies.)

However, Moodle@GSN appears not to have worked in that there has been a high

level of passive participation, that is absence of posting, for more than three years

(1077 days on the 13/10/2006 according to the log files). Although the Greek

teachers do visit and download material as apparent from the log files, there is no

evidence that the Greek teachers use the e-learning service effectively and skilfully to

transform information into knowledge. Following one of the participants in one of the

studies “absence of participation in GSN is probably because (desire, time, money

for) planning and organisation are lacking. Collaboration in design and planning by all

stakeholders to bring pedagogy and technology together is lacking as the most

valuable idea/suggestion: learner / user involvement in the design”. It also appears

that broad collaboration is now crucial for contemporary organisations.

Even though e-learning has delivered mixed results, some advantages have been

reported in using e-learning for teachers’ training (Golian, 2000): e-learning is

individualised and self-paced; there are more opportunities to access learning

resources; e-learning is based on activities and experience (active and experiential

learning) within groups and communities (collaborative learning); time and cost are

less because of the use of the electronic form of resources; and communication is

nonlinear. Nevertheless, there are several obstacles: institutional, instructional,

technical, and personal (Piotrowski & Vodanovich, 2000).

1.3 QUALITY IN ONLINE EDUCATION

Online Education can support employees’ new competencies and training.

However, despite the huge investments in technology and e-infrastructure, and the

high levels of interest among educators, administrators and policy makers worldwide,

e-learning remains an unproven experiment. Nevertheless, the collapse of several

initiatives may not indicate the failure of the e-learning concept per se but rather a

lack of quality. The questions that arise are related to what constitutes e-learning

quality, why it is important, and whether quality assurance is feasible.

In general, quality refers to fitness for purpose, and in this context as applied to

learning (Stephenson, 2005). A survey on e-learning quality for CEDEFOP, the

European Agency for Vocational Training, showed that 61% of the 433 respondents

rated the overall e-learning quality somewhat negatively, as ‘fair’ or ‘poor (Massy,

2002:3). The European Foundation for Quality in eLearning (EFQUEL) conducted a

European survey between 15 August 2004 and 15 November 2004 (Panorama

Report, Ehlers, et al., 2005). In this survey, 5,023 people called up the questionnaire,

of whom 28 % actually completed it, and a further 7% finished the two basic sections

on quality in e-learning. According to the results, quality relates to obtaining the best

learning achievements (50%) and ‘something that is excellent in performance’ (19%).

In brief, the PANORAMA report revealed the importance of e-learning quality: the

need for critical awareness; the need for specific analytical frameworks as the

respondents although believed that they knew about quality they showed a general

lack of information; and the need for quality requirements in e-learning design. The

researchers stressed that ‘learners must play a key part in determining the quality of

e-learning services’ and insisted on the involvement of all e-learning participants in

quality design and development by 2010 (p.11).

Overall, design for socio-cultural learning appears to be connected to e-learning

quality; this is not only a Greek but also a global phenomenon. Socio-cultural

learning is related to e-learning systems and tools used to facilitate and support

socio-cultural learning principles and in particular collaborative learning. UNESCO’s

definition suggests that collaborative learning takes place:

when learners work in groups on the same task simultaneously,

thinking together over demands and tackling complexities.

Collaboration is here seen as the act of shared creation and/or

discovery. Within the context of electronic communication,

collaborative learning can take place without members being

physically in the same location.

Technology & Learning definitions, UNESCO (n.d.)

This means that collaborative learning is related to co-creativity and has the potential

to occur online. Therefore, interventions to support social interactions, collaborative

learning and associated tools may influence e-learning quality. It also suggests that if

one of the elements is missing then e-learning quality may be impaired.

1.4 AIMS AND RESEARCH QUESTIONS

The problem this research addresses is the lack of e-learning quality as

evidenced by the Greek teachers’ passive participation in e-learning communities.

Since this appears to be a common problem it is worth investigating. Thus, the goal

of this thesis is to shed light on passive participants in e-learning communities and

propose conceptual frameworks to ensure their participation. More specifically, this

study aims to carry out the following in regard to Collaborative e-Learning

Communities:

The study translates into two sets of questions in order to study the conditions to

tackle e-learning quality. The first set of research questions will be investigated in the

literature review. These are:

Q1. In what ways can studies of Collaborative e-Learning Communities (CeLC)

be exploited in a concrete way by educational designers?

Q1.A. In what ways has collaborative learning research evolved up to the

present?

Q1.B. Are there any collaborative e-learning frameworks to support CeLC?

Q2. Is there an educational design approach that can ensure quality in specific

e-learning contexts such as the Greek teachers’ community?

Q2.A. What is design?

Q3.B. Are there any design principles for specific educational contexts?

Q3. Are there any tools and techniques that can be used to facilitate the

formation of CeLC? If so, what are the effective characteristics and usage of

these tools?

Q3.A. Are tools and techniques for evaluating participation helpful to enable

participation?

Q3.B. Are tools for observing and analysing interactions helpful to enable

participation?

The second set of questions has an exploratory nature and will be based on the

previous results:

1. Collaborative e-Learning Communities (CeLC) Q1.Ex1. Is there a collaborative learning scheme to identify, analyse and

evaluate CeLC?

Q1.Ex2. Are there any evaluation techniques that can be used to facilitate the

formation and maintenance of CeLC?

2. Educational Design

Q2.Ex1. In what ways can core design principles be integrated in the process

of educational design?

Q2.Ex2. In what ways can quality by design be achieved for the Greek e-

learning communities?

3. Tools to Support CeLC

Q3.Ex1. Are tools for evaluating participation helpful to enable participation?

Q3.Ex2. Are tools for structuring collaborative learning helpful to enable

participation?

Q3.Ex3. Are tools for observing and analysing interactions helpful to enable

participation in the Greek e-learning community?

Q3.Ex4. Are tools for observing reporting information on interactions helpful in

enabling participation in the Greek e-learning community?

1.5 OVERVIEW OF THE CHAPTERS

The chapters in this thesis are developed as follows:

Table 1.5-1. Chapters Overview

TOOLS AND EVALUATION TECHNIQUES FOR COLLABORATIVE E-LEARNING COMMUNITIES

Chapters Description

1 Introduction

Motivation, research problem Aims and objectives Research questions Chapters overview

2 Literature review

Collaborative e-learning E-Learning communities and participation Tools and evaluation techniques Design Conceptual framework

3 Research design Research methodologies

4 Research context Understanding the research context Ethnotechnological inputs Preliminary studies

5 Tools and evaluation techniques Planning and design

6 Main study Implementation of previous conceptual frameworkFindings Discussion

7 Conclusions

Summary of the Thesis Conclusions Recommendations Future trends

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Delich, P. (2006). Pedagogical and interface modifications: What instructors change after teaching online. Published doctoral dissertation, Pepperdine University, Malibu, CA. Retrieved 10/09/2007, from http://proquest.umi.com/pqdlink?Ver=1&Exp=09-09-2012&FMT=7&DID=1144195631&RQT=309&attempt=1.

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Ehlers, U., Hildebrandt, B., Görtz, L. & Pawlowski J. (2005).Quality in European e-learning – PANORAMA report. A study by the European Quality Observatory. Retrieved 12/11/2006, from http://cms.eun.org/shared/data/pdf/quality_in_e-learning_panorama_en.pdf.

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Franklin, S., Peat, M., Lewis, A., & Sims, R. (2001). Technology at the cutting edge: A large scale evaluation of the effectiveness of educational resources. Paper presented at ED-MEDIA, the 13th Annual World Conference on Educational Multimedia, Hypermedia & Telecommunications. 25-30 June 2001, Tampere, Finland.

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Schlager, M., & Fusco, J. (2004). Teacher professional development, technology, and communities of practice: Are we putting the cart before the horse? In S. Barab, R. Kling, & J. Gray (Eds.), Designing for Virtual Communities in the Service of Learning. Cambridge, UK: Cambridge University Press. Pp. 120-153. Retrieved 22/05/2006 , from http://tappedin.org/tappedin/web/papers/2003/TPDBarab.pdf.

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WR Hambrecht & Co (2000). Corporate E-learning: exploring a new frontier. Retrieved 14/03/2006, from http://www.astd.org/NR/rdonlyres/E2CF5659-B67B-4D96-9D85-BFAC308D0E28/0/hambrecht.pdf.

Tools and Evaluation Techniques for Collaborative E-Learning Communities Chapter 2: Literature Review

Literature Review: Design for Collaborative e-Learning Communities

• Why collaborative learning is important for today’s e-learners

• How and why educational research moved from the study of the individual to the study of the community

• Participation in online and e-learning communities

• How design supports the user as a learner within a community

• The need for further investigation for tools and evaluation techniques to support collaborative e-learning communities

• New propositions

Chapter 2 discusses the importance of collaborative learning to effective e-

learning. Collaborative learning research as well as current design for e-learning

suggest that the research focus has evolved from the study of the individual to

the study of the community. However, there are still questions about instructional

design as well as quality in e-learners’ interactions. Investigation of the literature

pointed to new propositions for tools and evaluation techniques to enhance

participation in collaborative e-learning communities.

2.1 INTRODUCTION

Education as a discipline was initially anchored in Cognitive Psychology

and Pedagogy. Only recently, has learning with the use of tools introduced

design issues. This chapter attempts to shed light on the multidisciplinary nature

of e-learning, to explore its social nature and the role of tools in collaborative e-

learning communities.

2.2 COLLABORATIVE LEARNING

According to Lave (1988:1), cognition is a complex social phenomenon

that occurs within the individual’s head. It refers to intermediate variables that

describe social interactions and their relationships with the conditions that

facilitate learning. Because the intermediate variables are invisible, their

observation and study is difficult. However, it is possible to study human activity

and inference from this cognitive change. Activity in the form of discussion of

shared experience has been considered an effective means for adult learning

(e.g. Brookfield, 1990; Brown & Duguid, 2000). Nonetheless, participation in

discussions can be active, where the individual participate by posting, and

passive, where the individual does not. Consequently, without active participation

passive participation is not possible.

Other than the importance attached to socio-cultural learning, collaborative

learning as well as passive and active participation in dialogue are concepts also

related to recent approaches to adult learning. Knowles (1984) proposed the

theory of andragogy (adult learning) to complement pedagogy (child learning):

adults were responsible for their learning; there should be specific targets relative

to their backgrounds; instruction should be task oriented; and discovery should

be guided and facilitated thus the relationship between the instructor and the

learner needs to be redefined. In reality, adults not only accept but also pursue

passive learning (Rogers, 2002; Jarvis, 2004). Mezirow (2000), in his theory of

transformative learning, proposed that adults were reflective, critical, and open to

others’ opinions; thus, active participation in groups was essential. However,

external factors such as organisational and financial problems could be major

obstacles (e.g. Brookfield, 2001); additionally, adults were less flexible towards

change and for this reason, they did not acknowledge their passive participation

(Illeris, 2002). Nonetheless, Mezirow proposed that dialogue, the collaborative

learning pillar, was the solution.

Two terms have been used interchangeably in collaborative learning history:

cooperation and collaboration. Cooperation was the basis of sociability “acting

together, in a coordinated way at work, or in social relationships, in the pursuit of

shared goals, the enjoinment of the joint activity, or simply furthering the

relationship” (Argyle, 1991:15). (Johnson & Johnson, 1994 provide an overview

on cooperative learning.)

An attempt to propose a distinction between cooperation and collaboration was

made by Teasley and Roschelle (1993):

Collaboration is a coordinated, synchronous activity that is the result

of a continued attempt to construct and maintain a shared conception

of a problem… Cooperative work is accomplished by the division of

labour among participants, as an activity where each person is

responsible for a portion of the problem solving.

Teasley & Roschelle, 1993:235

Teasley and Roschelle provided a clear distinction anchored in the idea that

tasks are divided between participants: “each person is responsible for a portion

of the problem solving”. However, such division is not deliberately required from

the participants, although roles exist naturally as a spontaneous division of

labour. In their review, Borgers and Baranauskas (2003) advocated collaborative

learning as it had more advantages than other types of group learning. It

empowered and enabled learners to solve problems and understand subjects

more easily since discussing ideas and constructing arguments through dialogue

could shape in-depth learning. Collaboration is an interactive process that

engages two or more participants working together to achieve outcomes they

could not accomplish independently (Salmons & Wilson, 2008). UNESCO’s

definition embraces most of the aforementioned concepts; collaborative learning

occurs

when learners work in groups on the same task simultaneously,

thinking together over demands and tackling complexities.

Collaboration is here seen as the act of shared creation and/or

discovery. Within the context of electronic communication,

collaborative learning can take place without members being

physically in the same location.

Technology & Learning definitions, UNESCO (n.d.)

Thus shared creativity for new knowledge building is the ultimate collaboration

learning target that can also be expanded to online settings. Working on shared

tasks implies learners’ participation and engagement.

However, some e-learners do not actively participate but lurk1. According to the

Free Online Dictionary for Computing (http://foldoc.org, added on 14/06/1997),

lurking is a messaging jargon for activity of one of the "silent majority" in an

electronic forum; it is posting occasionally or not at all, but reading the group's

postings regularly. This term was not pejorative; for example, reading the

Frequently Asked Questions was recommended netiquette for beginners who

needed to learn about the history and practises of the group before posting. This

distinction of passive and active participation appeared in computer-supported

tasks; the participant who controls the mouse tended to be "executor", while the

other was likely to be the "reflector" (Blaye et al., 1991). According to Miyake

(1986:174): "The person who has more to say about the current topic takes the

task-doer's role, while the other becomes an observer, monitoring the situation.

The observer can contribute by criticising and giving topic-divergent motions,

which are not the primary roles of the task-doer." Miyake referred to active as

well as reflective learning since criticism could support new knowledge

production.

If passive and active modes are acceptable, there should be some processes

and pedagogical methodologies to create and maintain the transition between

these. Rather than the facilitator or educator providing rules for learning (Berge &

Collins, n.d.; Wegerif, et al., 1998:495), learners took responsibility for their own

learning, as, according to Mercer (1995), they had to: talk to create the context;

engage in collaborative learning activities; create common knowledge; and follow

ground rules that encourage the exchange of relevant ideas and active

participation. Initial intention is another prerequisite, important enough to form a 1 Passive participation and lurking will be used interchangeably in this thesis as a demand for changing the term lurker was observed in the literature as well as online communities and conferences (e.g. E-mint community, the JISC, Joint Information Systems Committee online conference discussions on ‘Innovating E-Learning’, http://www.jisc.ac.uk/elp_conference07).

cooperative principle needed before interactions occur (Grice, 1975). This idea

was further developed in psychology as the principle of the “least collaborative

effort” (Clarke & Wilkes-Gibbs, 1986:26), as an active concern for the

construction of mutual understanding in order to develop a shared focus and a

shared narrative (Crook, 1994:176). In other words, it is the e-learners’ shared

goals and generated context that make collaborative learning occur; then,

collaborative e-learning continuity creates the shared narrative that fabricates its

history and builds a successful e-learning community. Prerequisites also refer to

a joint interactive space for grounding, as interactions intended to create

common ground (Clark et al, 1983), mutual understanding, knowledge, beliefs,

assumptions or presuppositions (Baker et al., 1999; Mäkitalo et al., 2001) or

“repairing” misunderstandings (Dillenbourg, 1999). Therefore grounding is built

on sociability. This means that sociability creates the initial conditions for

collaborative learning.

Overall, it appears that sociability is the basis for collaborative learning

supporting both a reflective and active mode. Shared goals and activities,

cooperation and collaboration through dialogue, spontaneous roles and division

of labour, co-creativity as exploration and discovery, and enjoinment of the joint

activity are concepts found in collaborative learning. According to Dillenbourg

and colleagues (1996), the key to supporting collaboration is to find suitable

intermediate variables to describe and support collaborative interactions and their

relationships with the conditions that facilitate collaborative learning.

2.2.1 From the Individual to the Community:

a Brief History

Dillenbourg and colleagues (1996), said that the development of an

understanding of collaborative learning began with the learner as an individual;

then it moved to group learning in a more socio-cultural mode, and finally,

expanded to the community. During the 70s and early 80s, research was focused

on the individual’s learning processes. The context of their interaction was seen

as a backdrop rather than the focus of research in its own right. When the group

became the unit of analysis, the focus shifted to the social construction of

knowledge; however, this was still on the basis of studying individuals. In terms

of empirical research, the focus was on comparative processes to establish

whether and under what circumstances collaborative learning was more effective

than learning alone. Because collaborative learning is inherently complex, it was

almost impossible to establish causal links between the conditions and the

effects of collaboration. Therefore, Dillenbourg and colleagues indicated the need

for new tools and methods for observing and analysing interactions to increase

understanding of the collaborative learning social mode. This development of an

understanding of learning is briefly presented next.

In Piaget’s early writings (1932), the potential productivity of peer interaction in

relation to cognitive development was related to the achievement of concrete

operational modes of thought in the early years. Egocentrism was the main

obstacle to operational thinking and requires its “decentralisation”. This is the

ability to take into account multiple points of view and multiple covarying factors

in a given situation. One of the fundamental concepts that helped collaborative

learning to evolve was the socio-cognitive conflict derived from the interaction

with other learners as a result of decentralisation. Socio-cultural researchers

were able to build on the egocentric thought as the inner dialogue, and expand it

with the outer dialogue required in socio-cultural contexts.

The second major theoretical foundation that influenced collaborative learning

was the socio-cultural approach. In brief, it advocated that knowledge acquisition

was based on the alignment of asymmetrical interactions between learners and

more capable peers (Vygotsky, 1962, 1978). The research focus was shifted to

the causal relationship between social interaction and individual cognitive change

stressing the importance of social activity within a group to promote cognitive

development. Dialogue as social speech was the medium of communication, and

inner dialogue was the medium for self-regulation. To Light and Littleton (1999),

Vygotsky’s work introduced two significant concepts, the “zone of proximal

development” (zpd) and “scaffolding” (Wood, Bruner & Ross, 1976); the

individual could reach a higher level of development with the help of a more

capable other. Socio-cultural learning attached significance to the level of

symmetry/asymmetry between the members of a group. In fact, Tharp and

Gallimore (1988) suggested that peer assistance at the same level of asymmetry

is required so that peers can help themselves. The individual often gets more of

a chance to participate actively in critical planning and decision making when

interacting with an expert tutor, more capable peers or other peers. Studies on

this relationship led to the community knowledge building approach (e.g. Lave &

Wenger, 1991). Here, the learning process occurred within a larger physical and

social context of interactions and culturally constructed tools and meanings.

Social and individual were not different levels of study but inexorably

interconnected; this created two distinct traditions of situated cognition, one

focused on the individual and a second focused on community (Wilson & Myers,

2000). The community focus is next. There were several community definitions; for example, Peck (1987) stated that

“If we are going to use the word [community] meaningfully we must restrict it to a

group of individuals who have learned how to communicate honestly with each

other, whose relationships go deeper than their masks of composure, and who

have developed some significant commitment to "rejoice together, mourn

together," and to "delight in each other, make others' conditions our own." The

development of communication channels, trust, support, and a sense of

belonging seemed to be significant to help a community to emerge. Lazlo and

Lazlo (1997, 2000) described the community as a group of two or more

individuals with a shared identity and a common purpose, committed to the joint

creation of meaning. The authors echoed Lave and Wenger in Communities of

Practice (CoP) (1991); CoP members shared the characteristics of joint

enterprise, mutual engagement and shared repertoire to clarify, define, and

evolve practices (Wenger, 1998). One implication of the social reproduction of

CoP was that the sustained participation of newcomers, as they become old-

timers, must involve conflict between the forces that support processes of

learning and those that work against them. This was because learning,

transformation, and change were always mutually present. Thus, CoPs were

engaged in the generative processes of producing their own future. Learning in

communities was configured through the process of becoming a full participant in

practice and being able to get involved in new activities, perform new tasks and

functions, and master new understandings.

Thus learning is the process of participating in communities. It was proposed that

this centripetal process of engagement was proposed to be legitimate for all

participants. Lave and Wenger (1991) called this learning process Legitimate

Peripheral Participation (LLP). More specifically, LPP was a decentred model

where a specialist field contained different levels en route for newcomers’

engagement and practice. The peripheral members drifted into the centre as their

interests were stirred. Thus, there were hierarchical levels of engagement

depending on many factors, both external and internal to the participants. The

newcomers were located at the first level, as potential contributors, and were not

voiceless or powerless but a vital part of the community. Overall, Lave and

Wenger proposed that LPP was a descriptor of engagement in social practice

that entailed learning as an integral constituent. In fact, central and peripheral

participation should not be on different levels after all (1991:35). The next table

describes CoP, the research focus, the key tenets, the research methods and

results (Table 2.2.1-1):

Table 2.2.1-1. The Socially-Shared Cognition Approach: Communities of Practice

Communities of Practice (CoP)

Research Focus Key Tenets Research Methods Results

-The individual, the social and the physical is one research context. Learning is a process of participating in CoP. Research Questions What is learning within a community? Is learning via interactions with other individuals more efficient than learning alone? What are the types of social engagement that facilitate learning? What are the social conditions that facilitate learning?

-Learning is situated and grounded in everyday actions. -The situation needs to be studied as a whole. -CoP characteristics: joint enterprise, mutual engagement, shared repertoire -Legitimate Peripheral Participation increases in engagement, complexity and responsibility. -Learner’s participation in the community lies in the concept of “becoming part of the community. -Lurkers are legitimate participants and community members. -Tools are part of the community’s heritage and cultural life.

-Inter - disciplinary research -Real settings -Ethnographic inputs

-There are different types of communities. -Conflicts may allow resolutions. -The conditions that facilitate participation: -management of the participation process -accessibility to information, & -tools that enable members’ participation and learning.

It appears that the research focus involved the individual, the social as well as

their situated context where the individual participates in collaborative practices.

For this reason, multidisciplinary methods needed to be evolved to investigate

learning on an individual and social level as well as the tools and the

environment of participation. Thus, the sense of belonging appeared to be the

driving force for collaborative learning enhanced by tools.

A project focused on lurking in CoP that accommodated community

management, explored the meaning of “legitimate peripheral participants”

(McDonald, 2003) viewed as occurring in separate levels (Figure 2.2.1-1):

Figure 2.2.1-1: The Eyeball of Participation

The participants were located in four levels, based on the “numeric amount” of

posting to the community (number of messages). With a direction from the

periphery to the centre, lurkers were the participants who did not exhibit any

activity. On the second level there were the members who occasionally

contributed to the community. The participants and key contributors were located

on the third and fourth level. The “eyeball of participation” provided a structure to

better understand legitimate peripheral participation. McDonald and colleagues

stressed the fact that the active members are the ones who “add value” and fill

the gaps for all members in order to sustain the community.

Learning in communities was built on social interactions. Identity (e.g. Donath,

1996; Lee et al., 2006) and the sense of belonging (Nonnecke, 2000) appeared

to be essential concepts in community research. In fact, the latter was suggested

as the basic factor that distinguished a guest from a member in an online

community and was initially studied in relation to empathy2 (e.g. Preece, 1999,

2 Empathy is a “complex psychological inference in which observation, memory, knowledge and reasoning are combined to yield insights into the thoughts and feelings of others” (Ickes, 1997:2)

2004; Preece & Ghozati, 2001; Lambropoulos, 2005a, 2005b). Nonnecke and

Preece (2000:127) found that some lurkers felt a sense of community, especially

when the dialogue engenders “a sense of trust and care”; this was an indirect

way to become active contributors. Lambropoulos found that the members who

developed empathy became active participants (2005a). Ramachandran

suggested that empathy was a cognitive activity triggered by the mirror neurons

(2000) and appeared to be a key in human communication regardless of the

medium used.

2.3 ONLINE & E-LEARNING COMMUNITIES

While educators and learners in classroom-based courses have

already discovered the benefits of an engaged learning approach to

education, the power of engagement in online courses is yet to be

fully realised.

Conrad & Donaldson, 2004:ix

After Rheingold’s book ‘The Virtual Community’ (1993), the idea of

simulating a community remained popular. Researchers had examined a range

of phenomena related to online and text-based discussion groups including

member contribution patterns, sustainability, and motivations to contribute (e.g.

Rheingold 1993; Constant et al, 1996; Nonnecke, 2000; Wasko & Faraj 2004;

Gulati 2006; Butler et al., 2007). An online community referred to people who

make the community where group dynamics, needs and roles shaped the

community; purposes, that is people come together for a purpose(s); and policies

that is the behaviour governed by group norms, rules and sometimes formal

policies (Preece, 2000). Furthermore, software was needed to mediate, support,

and influence or restrict community activity. A community is something more than

merely an aggregation of users using a collection of communication tools

(Typaldos; 2000) As for e-learning communities, these explicitly target learning,

e-learning leaders agreed that interaction was the key for their effectiveness (for

a review see Conrad & Donaldson, 2004).

Research on e-learning communities appeared in the mid 80s (e.g. Hiltz, 1985).

However, Barab and Duffy (2000) argued that e-learning environments were

practice fields rather than authentic Communities of Practice (CoP) because the

activities were not real; they were educational and not part of the communities’

authentic work. On the other hand, being a participant in a community was an

essential component of the educational process (Goodfellow 2003): ‘communities

of practice’ differ from ‘communities of learners’ in that the latter are reflexively

concerned with learning whereas the former are concerned with practice, of

which learning is a corollary. (p. 3). It appears that there is a difference between

online CoP and e-learning communities. Active and passive behaviour is not a

new phenomenon; an experiment on active and passive reading was conducted

by Janis and King in 1953 (cited in Hovland et al.1953). Two experimental groups

of college students worked as ‘active participants’, who delivered talks in a group

situation; and ‘passive controls’, who read and listened to the source material.

The results indicated that all members had the potential to become active

participants; in other words, they were located in the grey zone of potential active

participation. This grey zone was characterised by the “sleeper effect” as a

change of behaviour after a lapse of time (Hovland et al., 1953). If all passive

participants have the potential to become active this requires an effort on their

behalf.

The Greek teachers belong to an off-line CoP; however, this community is not

reflected in an online CoP. For this reason passive participation has been

identified as the key variance in this study. Thus, the Greek teachers remained

on the first level of participation, that is passive participation. This variance is

imperative to be controlled on a pedagogical and operational level. The question

that arises is, if the Greek teachers do belong in an offline CoP why is it so

important to force them in active participation in collaborative e-learning

communities?

Participation in CoP involves the use of tools; artefacts used within a cultural

practice carry a substantial portion of that practice's heritage. Thus,

understanding the technology of practice is more than learning to use the tools; it

is a way to connect with the history of practice and participate more directly in its

cultural life (Lave & Wenger, 1991:100-102). In the age of ubiquitous computing

and the social phenomenon of the Web, and with the growth of what Berners-Lee

(2007), calls collaboration and creativity, communities will continue to evolve.

Thus, the question is not why it is important to engage the Greek teachers in e-

learning, but finding ways to enable it.

2.3.1 Passive Participation in Online

Communities

Some online communities’ members act as invisible observers of

synergetic activities; they never seem to cross the threshold of observation and

remain in the periphery (e.g. Nonnecke & Preece, 1999; McDonald, 2003; Gulati,

2006). (For a review see Schultz & Beach, 2004.) Nonnecke and Preece (1999)

suggested that ‘lurking is a systematic and idiosyncratic process, with well-

developed rationales and strategies. All interviewees lurked, but not all the time,

and several developed a sense of community through their lurking.” In other

words, lurking is personal and situated; at a particular time an individual is

located within specific external and internal conditions that create reasons that

affect his/her online behaviour and performance. A lurker can generate the sense

of belonging but is it enough?

Posting and interactivity have come under research scrutiny early in online

research (e.g. Rafaeli, 1986; Bruckman & Resnick, 1995) where interactivity was

related to dependency among messages (Rafaeli & Sudweeks, 1997). Figures

related to interactivity and passive participation are different, depending on the

dynamics of the media, and result in specific lurking behaviours (e.g. Fish et al.,

1990; Whittaker et al., 1998; Monthienvichienchai, 2004). Passive participation

can be tracked approximately using different methods provided that the software

supports it, for example counting the views (e.g. Nonnecke & Preece, 2000) or

using proprietary tools that log lurkers’ communicative behaviour (e.g. Soroka, et

al., 2003). Carroll & Rosson (1996) referred to lurkers-to-posters ratios 100:1,

Sproull and Faraj (1997) reported an 80% of lurking, Preece from 46% to 82%

(2000) and Lambropoulos, working with a Greek teachers’ online community,

99% (2002). Lurkers in one community can actively participate in other

communities where they believe they have something important to say (Klemm,

1998).

Nonnecke, in his PhD Thesis (2000), increased understanding of online lurking

by addressing three primary questions: why lurkers lurk, what lurkers do, and

how many lurkers there were at the time of the investigation. The primary reason

for passive participation was uncertainty about the community’s goals. Most of

the reported reasons fell into the personal sphere. Preece and colleagues

reported the top five reasons for lurking (2004): not needing to post; needing to

find out more about the group before participating; thinking that they were being

helpful by not posting; not being able to make the software work; and not liking

the group dynamics or the community was a poor fit for them. Social loafing or

free riding (e.g. Kollock & Smith, 1996; Wellman & Gulia, 1999; Ling et al., 2005)

proposed to be a robust phenomenon that occurred when people work less to

achieve some goal when they thought they were working jointly with others. This

is a limitation on lurkers’ research as free riders might never have responded.

(For example, Preece and Nonnecke’s survey response rate was 2.3%.)

Although passive participation is common and normal there is a contribution

paradox: even though passive participants may feel a sense of belonging, and

their participation is not a prerequisite; it is necessary for the life of the

community.

2.3.2 Passive Participation in e-Learning

Communities

Studies of passive participation initially targeted online communities, then

e-learning communities. In comparison to online communities, it appears that the

major reason for being a lurker is a lack of knowledge of how to take part

effectively.

Passive participation was observed for discussion forums or blogs (Williams &

Jacobs, 2004); the relationship between writing and reading behaviour (Ebner &

Holzinger, 2005); if activity influences learning efficiency (Beaudoin, 2002); or

underlying assumptions of e-learning pedagogy (Gulati, 2006). In particular,

Beaudoin (2002) found that almost 23 out of 55 (42%) of online education

master’s degree students, preferred to read other learners’ messages. A

questionnaire sent via email to 23 "low visibility or "no visibility" learners (p. 150),

showed that e-learners were: reading assignments and others’ comments;

conducted web searches; writing assignments; and spent least time on writing

comments for online discussions. Other observed behaviours were: connecting

(visiting the community); browsing (passively participating in community’s life);

attending time durations; contributing opinions; responding to specific posts; and

interacting (responding in a reciprocal manner) (Rafaeli et al., 2004).

Although passive participation is legitimate, the situation seemed to be more

complex in e-learning if passive participants were beneficiaries of other people’s

discussions who did not share their own ideas (Salmon, 2000). Reasons for

lurking were related to the individual, the community, the tools for

communication, and research methodologies (for a review see Rafaeli et al.,

2004). Beaudoin found that 40% (n=23) were not sure how to articulate their

ideas, 30% did not understand the topic, 30% did not know what to say as the

discussion drifted away from the topic, and 25% said that they were not

comfortable in presenting their ideas online. These e-learning managerial

reasons may be related to reasons inherent in the teaching and learning modes

(e.g. Klemm, 1998; Earley & Gibson 2002). Klemm (1998) advocated that there

were psychological and social reasons with roots in the passive conditioning and

the “entertain me” mode of mass media. Both learners and teachers had been

exposed to television and traditional classroom teaching that deprived them of

critical thinking. In particular, Klemm, working on an online conferences context,

believed that lurking restricts creative thinking and teachers foster this behaviour

with their practices. To Khine and colleagues (2003) there is trainee teachers’

inability to actively participate in online discussions; the participants were not

critical thinkers and failed to sustain interaction. E-learners have been found

reluctant to criticise each other (Hughes & Daykin, 2002:222) even if they are

“forced” to be active (e.g. Williams, 2002; Oliver & Shaw, 2003). Greeks are not

different; in fact, Buhayer (2005) referred to the Greek media as transmitting a

model of a reluctance to follow the stories through, lack of investigation and

questioning that killed conversation in Greek homes (p. 157-158).

In her PhD research, Gulati (2006) suggests that passive participation is an

informal mode of learning and an essential part of formal education. She

opposed the controlled and structured type of e-learning that considered lurking

as dysfunctional and problematic. She said that the e-tutors do not have a

problem with lurking; the problem lies in their inability to display lurkers’ learning

in order to justify their existence. Furthermore, she suggested that compulsory

contributions proved inadequate in increasing collaborative learning since it was

connected to Foucault’s (1984) discourse of normalisation through policing. In

other words, compulsory contributions tried to police and repress the outlaws, the

lurkers. The role of the learner was more concerned with what an individual

constructed as an engaging process, so ‘visible’ and ‘silent’ roles were personal

constructs, and were enacted in order to understand the world and showed how

individuals constructed their own perspectives. She concluded that there was a

need to open the concept of learning and include silent, unmeasured learning;

redefining participation in learning allowed an open understanding of adult

learning. The reasons for passive participation are summarised next (Table

2.3.2-1):

Table 2.3.2-1. Reasons for lurking in e-learning communities

REASONS FOR LURKING IN E-LEARNING COMMUNITIES

Personal Social Software limitations

- lack of awareness about informal learning, -deep or surface views -different perceptions of what was required -familiarization with the community -learn about a new topic -being shy -information overload -lack of recognition informal learning -differences on goals -differences in processes -different perceptions of what is required from learners

-differences in learners’ goals, processes and engagement approaches -access to best practices -organizational obstacles -inconvenient procedures -security considerations -community-knowledge building as a public good -integration of novices into work environments -unite geographically dispersed work units

-inadequate learning platforms

Lack of awareness about informal learning, different levels of understanding and

differences in e-learning targets were the main reasons for passive participation.

This implies that e-learners were unaware of tools and techniques. Social

reasons were identified as differences in goals, processes, engagements

approaches, access to best practices and organisational obstacles. In addition,

Rafaeli and colleagues (2004) suggested that personal characteristics, such as

being shy, information overload, organizational obstacles, inconvenient

procedures and security considerations increased passive participation. This

means that appropriate community management can tackle these problems;

however, there is nothing that can be done for the organisation obstacles,

procedures or security problems. Based on the reasons for lurking, researchers

developed strategies for active participation (Table 2.3.2-2):

Table 2.3.2-2. Active Participation Strategies

STRATEGIES TO ACTIVATE PARTICIPATION

Authors Active Participation Strategies

Klemm (1998)

-require participation, -form learning teams, -make an activity interesting, -do not settle for just opinions, -structure the activity, -require a hand-in assignment as a deliverable derived from the discussion,

-e-tutors need to know what they are looking for and involve themselves to help make it happen -peer grading

Archichvili et al. (2003)

-set of institutional norms promoting trust, -promoting knowledge sharing as a norm of the organization, -employees are trusted, -sharing is a moral obligation. -building multiple face-to-face CoP -clear norms -standards for sharing knowledge. -obtain active participation

Swan et. al., (2003)

-have transparent interface, -importance attached to the role of the e-tutor, -valued and dynamic discussion

Rafaeli et. al., (2004)

-familiarity with the community -develop a sense of community

Strategies such as building e-learning teams were based on specific

methodologies to develop a sense of community in a trusted common space for

information sharing. Strategies also referred to community management and

members’ roles. E-learners, e-tutors, designers and engineers and the

organisation hold responsibility for planning and supporting e-learning activities.

For example, the e-tutor may structure collaborative activities while the

organisation can incorporate standards and rewards for sharing knowledge;

designers may provide transparent and usable interfaces, and engineers

contribute technical support. Overall, it appears that the key to participation is the

shape of collaborative e-learning design supported by suitable tools and

methodologies.

Overall, this section discussed the socio-cultural and pedagogical foundations of

participation in collaborative e-learning communities. The literature referred to

what reduces active participation. Since personal and social reasons refer to

community and learning management they can be tackled by aligning new tools

and evaluation techniques with pedagogical modifications. Such tools and

techniques need to support investigation for observation, description and

analysis of what happens in collaborative e-learning communities.

The next section will investigate whether current design supports them.

2.4 DESIGN FOR LEARNERS AS USERS &

USERS AS LEARNERS

Online Education is in its infancy and has yet to construct design models

that will address the problem of the learner as a user (Wallace, 1999; Smulders,

2003). Learning how to be a user is about understanding the technology rather

than learning to use the tools (Lave & Wenger, 1991:100-102). There is an

assumption that the educational systems are easy to use by the educators and

learners. Users in educational settings act as both users and learners and design

has to support their dual persona (Smulders, 2003). However, technologists tend

to build techno-centric systems for use by academics, this means integrating

several levels of functionality which is geared towards the e-tutors rather than

considering the e-learning participants. For example, besides the Greek teachers

and e-tutors, the Greek Schools Network (GSN) consist of developers, engineers

and decision makers. Additionally, today’s users are typically multi tasking; this is

especially so for younger users who might do homework whilst listening to Mp3s

and chatting with friends (Dede, 2005). In order to support multi tasking the

question of the interface becomes important since a usable system, one with an

easy to use interface, will enable users to concentrate on their tasks. Thus,

interface design might become pivotal and make the difference between a

system that is used and one that isn’t. Design may influence participation quality.

Many design definitions exist; for example, design underpins every form

of creation from objects such as chairs to the way we plan and execute our lives

(Dini, 2005). But to Suchman, design developed strategies and tools insensitive

to particular circumstances (1987:121) because plans actually derive after the

completion of the course. Such a post-hoc design structure challenged the

foundation of computational design as a linear process of development. It

appears that the design of new systems is always problematic.

2.4.1 Socio-Technical & User-Centred Design

Socio-technical design (STD) refers to design that is influenced by an

organisations’ social structure. In 1949, researchers from the Tavistock Institute

for Sociology in London formulated the most important principle for joint

optimisation of social and technical systems: if a technical system is created at

the expense of a social system, that is the organisation’s social structure, the

results obtained will be sub-optimal (cited in Mumford, 1983). According to

Mumford (1983), design should consider the social context and involve users

(socio-technical design). Faulkner (2000) suggested that systems should be

user-oriented in all aspects of their functionality by adjusting the systems to the

users and their natural environments (user-centred design).

Socio-technical design (STD) develops systems for collaborative working

environments. STD offered solutions to practical problems by fitting design to its

context. STD took the idea of designing for the user and the task a stage further

and endeavoured to design within the structure of the organisation and the way

in which it operates (Faulkner, 1998:134). Therefore acquisition of the ‘native’s

point of view’ was important and was provided by ethnography. Even though

STD provided schemes to fit design to its context, most designers were not

motivated by incorporating social structures into design (Anderson, 1997). In fact,

designers believed that it was user’s inability to cope with the system that was

the problem (Mumford, 1983). Nowadays designers acknowledge that the

development of interactive technologies relies on an appreciation of social

circumstances in which systems are used (e.g. Dourish, 2006). So, STD offered

key concepts for systems design such as participation in design, participation in

decision making, and the need for evaluation methodologies to support them.

STD considered the organisation as a whole. User-Centred Design (UCD)

provided a clear focus on users’ needs. These had to dominate the interface

design, and the interface had to dominate the design of the system. This was

achieved by a dialogue between the stakeholders and the developers and by

their involvement in the early planning stages. This is the purpose of UCD and is

what Shakel (1991) described as having the: “…capability in human functional

terms to be used easily and effectively by the specified range of users, given

specified training and user support, to fulfil the specified range of tasks, with the

specified range of environmental scenarios”. He suggested that systems need to

be used easily and effectively to support specific users; training and support on

the use of the system was central. UCD guidelines were needed to ensure

product quality even in the planning stages. Gould and Lewis (1985) proposed

four principles for useful and easy ways to create usable computer systems: (i)

early focus on users and tasks, (ii) empirical measurement for evaluation, (iii)

iterative design, and (iv) integrated design. When systems did not operate as

expected then user feedback should be sought and used in the redesign as

systems should conform to expectations. User-centred studies provided more

coherent frameworks and models for analysis of what is going on and what

should be done to ensure users’ satisfaction. Shackel (1991) suggested that

usability could be measured by examining learnability, effectiveness, attitude and

flexibility; Nielsen (1993) thought it was efficiency, learnability, memorability,

errors and whether the system is subjectively pleasing. The International

Organisation for Standardisation (ISO 9241-11, 1998) defined usability as a

measure of the quality of user’s experience when interacting with a system, in

terms of effectiveness, efficiency, and satisfaction. Measurements and

assessment procedures had to ensure the product met the purpose of design.

From an educational viewpoint, technology is to enable students to reach their

potential rather than technology being the goal itself. Educational designers

needed to consider not only the educational system as a whole but also the

learners’ dual persona as learners and as users, and facilitate learning without

any additional cognitive and physical struggles to use the system. Users of a

learning system needed to be free to learn the subject and not have to spend

time on learning about the system. In other words, the system must be usable

(Faulkner, 2000). Laurillard, in her interview with Neal for the E-learn Magazine

(2003) stressed this fact; she also said that there were critical issues for

technology enhanced learning and its future. More specifically, there was a need

to: adopt pedagogical perspectives; focus on user interface; build on learning

activities design; assess performance; and evaluate in the form of checking

whether the learning objectives have been met.

These recommendations have translated the user-centred design principles into

learner-centred design principles.

2.4.1.1 Towards a Learner-Centred Design

Educational design was built on the integration of the pedagogical and

technological levels, and was called Learner-Centred Design (LCD) or

Instructional Design. Whereas User-Centred Design focused on making users

more effective, LCD focused on making learners more effective. For Norman and

Spohrer (1996) LCD had three dimensions: (a) engagement as the result of

motivation, (b) effectiveness, and (c) viability of interventions. Engagement was

tightly associated with motivation, the provision of rapid compelling interaction

and feedback. Feedback was used to achieve effectiveness by measurement

and benchmarking. With a social perspective in mind, Squires and Preece (1999)

provided the first set of ‘learning with software’ heuristics echoing socio-technical,

user-centred, and learner-centred design.

‘Learning with software’ heuristics opened the way to learner-centred usability, or

Pedagogical Usability (PU) (e.g. Muir et al., 2003; Nokelainen, 2006). PU derived

as part of utility as software has high quality if users can perform their tasks (the

software is useful to them, Nielsen 1993). With utility in mind, Finnish

researchers (Silius et al, 2003; Nokelainen, 2006) proposed that PU should

question whether the tools, contents, interfaces, and tasks provided within the e-

learning environments that supported e-learners. For Silius and colleagues, PU

was tested with a questionnaire linked to the educational website. The

questionnaire targeted the suggested tools’ basic use and utility triangulated by

logs and data from the discussions anchored in pedagogical usability (Silius et

al., 2003a, 2003b). Muir and colleagues (2003) also worked on an e-learning PU

pyramid for educational effectiveness and practical efficiency of a course-related

website. They stressed the e-learning participants’ involvement in design,

evaluation, and decision making. (For a review of pedagogical usability attributes

see Nokelainen, 2006.)

Overall, educational systems and their integrated tools constitute the means by

which learners are permitted or restricted in the use of their learning capabilities.

Instructional design and engineering are design processes to ensure their

educational fulfilment.

2.4.2 Instructional Design & Engineering

Instructional Design (ID) is the systematic process of activities to solve an

instructional problem with the aid of technologies (Fenrich, in press). There were

different approaches in ID models (e.g. Molenda, 1987; Ryder, n.d.; Fenrich, in

press). For most instructional designers, the process fell into a framework called

ADDIE , that is analyze, design, develop, implement, and evaluate (Bichelmeyer

et al., 2005). Fenrich proposed a coherent ID model anchored in Bloom’s

taxonomy (1956) with practical guidelines targeted at instructional multimedia

solutions. ID begins with initialization and project planning (how the instructional

design is carried out), the design and development phase (appropriate strategies

and approaches in targeted contexts), and a quality assurance phase focused on

deployment, evaluation, and assessment. It also includes easy-to-use checklists

and presentation tips offering a comprehensive insight in ID and deployment

outside the control room. This interdisciplinary approach involved all stakeholders

in design by covering all stakeholders’ benefits defined under specific criteria:

roles, skills, characteristics, activities, commitments, and responsibilities. As with

the previous design approaches, identification of intents and planning based on

stakeholders’ goals, skills, background and characteristics provided the design

backbone. Fenrich said that his model works in ideal situations; in reality

instructional designers need to adjust the plan to given situations by integrating

evaluation results into system requirements and re-design specifications. This

means that Fenrich implicitly agreed with Suchman on the post-hoc nature of

design.

Instructional design and engineering are interrelated processes to support

planning, analysis, design, and delivery of a learning system. Instructional

Engineering (IE) integrated the concepts, the processes and the principles of ID,

software engineering and cognitive engineering (Paquette, 2004) and explicitly

referred to e-learning (Shepherd, 2001; Myrach & Knolmayer, 2005). Paquette

(2004) adopted Human-Computer Interaction (HCI) approaches directly into his

IE framework. His model described e-learning engineering in relation to:

engineering and re-engineering e-learning systems (macro design); producing

instructional materials (micro design); delivering training on networks; and

reviewing and maintaining e-learning. Paquette provided a complete knowledge

presentation system on platforms and portals and described all functions and

roles for the stakeholders called actors: the teacher-designer, the learner, the

facilitator, the manager, and the platform administrator. His MISA method was an

automated system that supported 34 main tasks and about 150 secondary tasks.

It has been developed continuously and tested successfully in different contexts

for several years.

However, it was suggested that systematic ID models had been accused of not

reflecting actual practice and not supporting new competencies for the 21st

century and post-industrial societies (Table 2.4.2-1):

Table 2.4.2-1. Instructional Design problems

INSTRUCTIONAL DESIGN PROBLEMS Authors Description

Visscher-Voerman et al., 1999; van den Akker et al., 2004 The ID process itself

Richey et al., 2000; Waters & Gibbons, 2004 ID competencies

Gordon & Zemke, 2000 Being cumbersome, ineffective, inefficient Gentry, 1994; Berger & Kam, 1996 The nature of the task

Seels & Glasgow, 1998; Shambaugh & Magliaro, 2005 Methods to inform practice

Tripp & Bichelmeyer, 1991; Fenrich, in press Costly to implement

Schwier, Campbell & Kenny, 2006

Not taking of advantages of new technologies

It appears that the major problem is related to the ID process itself with regard to

its implementation and flexibility. Some other problems related to e-learning

quality and recorded in the Panorama report (Ehlers, et al., 2005) were caused

by: e-learning participants’ unfamiliarity with the design process; division between

‘academic’ and ‘corporate’ approaches; lack of awareness of the need for quality

standards; the dual identity of the learner as a user was neglected; stakeholders’

engagement in the early stages of design was neglected; and the fact that design

in artificial settings makes it vulnerable to the Hawthorne effect, so little evidence

existed as to how to use technology effectively.

These problems were relevant to the situated nature of the learning environment

as they have a “conclusion-oriented” nature instead of a “decision-oriented” one.

In addition, social interactions were partially neglected; with the Web 2.0

signpost, instructional designers and engineers foresee the need of an e-learning

2.0 stage (Downes, 2006; Karrer, 2006; Jennings, 2005). At this point in time,

educational design needs to consider the social and collaborative structure of e-

learning communities for learners’ content creation. The question that arises is

not why ID and IE suffer from so many problems, but to what extent designers

need a more flexible or a more systematic model. Depending on the

organisational target, a managemental educational change suggests a more

open model, whereas design for particular systems requires a more coherent

model. According to Leigh (1998), instructional designers need to focus either on

one aspect of learning and instruction and act as consultants or matter experts.

Since the field is becoming too broad for most designers to work with authority,

these options give freedom to instructional designers. To answer this question,

following Winn (1986:20), “we must have at our disposal a whole battery of

methods to deal with the different types of things we need to find out”.

Overall, it appears that systems design can be the catalyst to overcome

variances or even crises. This implies that if design is relevant and suitable to

situation it can fulfil its purpose; then there is high probability not only of

overcoming the variance but reaching a high level of quality. The rest of the

literature review explores whether socio-cultural learning principles have been

incorporated in tools to support collaborative e-learning communities.

2.5 TOOLS FOR COLLABORATIVE

E-LEARNING COMMUNITIES

For active learning, point and click is not enough (Klemm, 1998).

Dillenbourg (2000) stressed the social aspect of e-learning as a designed

information space where learners are actors i.e. they co-construct the information

space. Kollock (1998) emphasised the need for such social computing: ‘The key

challenges the Internet community will face in the future are not simply

technological, but also sociological: the challenges of social interaction and social

organization.’. In other words, e-learning applications need to consider social

interactions between e-learning participants. So far, there are different types of e-

learning tools categorised under several criteria: temporal, as in synchronous,

asynchronous activities or both; the medium of communication as in text, audio,

visual, simulation and their combinations; the direction of activity as in broadcast,

email, messaging or interactive; web-based as offline or online; and the privacy

levels, these are public or private. The computer-based collaborative learning

tools are divided into conversation and collaboration tools. (For reviews, see

Conrad & Donaldson, 2004; Jonassen, n.d.; Kommers et al., 1992) Jonassen

said there was a chasm to consider between tools that support information

provision and groupware.

As for groupware, what supports collaborative learning is the visibility of the

collaborative learning structure, tools for observing interactions, and tools for

analysing interactions (Dillenbourg et al., 1996). Thus, design can impact

collaborative learning on the kinds of social interactions that aid learning since

aspects of software can modify the socio-dynamics between the learning

partners. Designing e-learning tools to influence collaborative e-learning has

methodological advantages. For example, such tools can give explicit control of

the process and support the type of interactions that were expected to promote it.

Lack of such tools results in lack of understanding collaborative e-learning and

vice versa. This is evident in current research by a lack of interesting papers

(Nick Rushby, editor of the British Journal of Education Technology, personal

communication via email, 06/12/2006). The question that arises is whether

collaborative e-learning tools can support the socio-dynamics of an e-learning

community.

The quest for tools in the e-learning history goes back to the 60’s. (For a detailed

view, see Moodle http://docs.moodle.org/en/Online_Learning_History, and

wikipedia http://en.wikipedia.org/wiki/History_of_virtual_learning_environments.)

Systems to support e-learning communities were not included in associated

reviews because they were considered as a “third place”, a room for social

collaboration outside home and work (Bruckman & Resnick, 1995). They were

also excluded from the history of online communities by Ambrozek and

colleagues (2004), and had a reference of 33 words in Preece and colleagues

(2000). The following graph from Google Trends depicts the separate routes of

the two terms in the literature (Figure 2.5-1):

Figure 2.5-1. Google trend history for online community and e-learning

The separate routes meet just before 2007 suggesting a trend within e-learning

communities. Nonetheless, the social aspects of collaborative e-learning were

apparent from the early years of the educational technology research. It is

interesting to observe that the word “collaborative” exists in early designs.

The social aspects of learning was scrutinised in Computer-Supported

Collaborative Learning (CSCL). There were early systems in the 70s such as the

Programmed Logic for Automated Teaching Operations (PLATO, Figure 2.5-2)

(Tuss, 2001; Van Meer, 2003) or a Time-shared, Interactive, Computer-

Controlled Information Television (TICCIT) (Bunderson, 1973).

Figure 2.5-2. PLATO III3

PLATO (Figure 2.5-2) pioneered concepts such as online forums, message

boards, learning management, online testing, email, chat rooms, instant

messaging, remote screen sharing, and online games.

In his review of e-learning software developments over the last 30 years, Rumble

(2001) proposed four models of teaching and learning: the transmission, the

constructivist, the socio-cultural, and the metacognitive model. Following

Rumble’s review, current LMS can be located only on the first three levels. In

other words, higher order thinking is not supported by current LMS. For example,

Moodle, related to this research, was based on socio-constructivist theories

(http://docs.moodle.org/en/Philosophy). Today, Moodle developers have

synthesized Rumble’s first three concepts in the “social constructionist

pedagogy”:

The design and development of Moodle is guided by a particular

philosophy of learning, a way of thinking that you may see

referred to in shorthand as a "social constructionist pedagogy".

Moodle, http://docs.moodle.org/en/Philosophy Last access

20/12/2006

3 Figure retrieved from the blog http://siliconuser.com/?q=node/12 - Posted June 8th, 2007 by Joshua Coventry (Permission to use the image in the Thesis was acquired via email on 06/12/2007.)

Despite the fact that the Moodle developers built on sound pedagogical

approaches, Moodle does not explicitly support collaborative e-learning

communities. Overall, it appears that current learning management systems have

not evolved significantly, compared to the pace of emerging technologies of

social networks and user-generated context.

2.5.1. When the Online Community Met

E-Learning

The first e-learning system that supported e-learning communities was

MediaMoo (Bruckman & Resnick, 1995). MediaMoo was excluded from the e-

learning history because it was a shared environment and set of activities for

people with the same research interests. MediaMoo community management

was heavily based on the members’ conversation as the primary activity.

MediaMoo became publically available in Jan 1993. MediaMoo developers saw

three aspects of an e-learning community: the platform, e-learning, and

community management. MediaMoo targets were explicitly referred to all

Rumble’s stages, the transmission, the constructivist, the socio-cultural, and the

metacognitive model and thus, ensuring the quality of participation in a

community by design. Kim, in an interview for Elearningpost (February 27, 2001)

about the design that ensures a successful e-learning community, said:

To create an effective learning community, you need to develop a social

and technical infrastructure that supports the key activity that's

happening there - which can be quite different for various online

learning communities.

Kim, 2001

To Kim, success is related to both the social and textual infrastructure for

situated activity and learner-created context. It also seems that more than ten

years after MediaMoo, a design to support socio-cultural e-learning is still an

issue.

2.5.1.1. Design Principles for E-Learning Communities

Researchers have proposed design principles for online and e-learning

communities since the early 80s (Table 2.5.1.1-1):

Table 2.5.1.1-1. Design principles for online and e-learning communities

DESIGN PRINCIPLES FOR ONLINE & E-LEARNING COMMUNITIES

Author Description

Axelrod (1984)

Requirements for the possibility of cooperation: • Arrange that individuals will meet each other again • They must be able to recognize each other • They must have information about how the other has

behaved until now

Ostrom (1990)

Design principles of successful communities: • Group boundaries are clearly defined • Rules governing the use of collective goods are well

matched to local needs and conditions • Most individuals affected by these rules can participate in

modifying the rules • The right of community members to devise their own rules

is respected by external authorities • A system for monitoring members' behaviour exists; this

monitoring is undertaken by the community members themselves

• A graduated system of sanctions is used • Community members have access to low-cost conflict

resolution mechanisms

Godwin (1994)

Principles for making virtual communities work: • Use software that promotes good discussion • Don't impose a length limitation on postings • Front-load your system with talkative, diverse people • Let the users resolve their own disputes • Provide institutional memory • Promote continuity • Be host to a particular interest group • Provide places for children • Confront the users with a crisis • Integrate the online environment with the "real" world

Kim (1998)

Principles for creating a community: • Define the purpose of the community • Create distinct gathering places • Create member profiles that evolve over time • Promote effective leadership • Define a clear-yet-flexible code of conduct • Organize and promote cyclic events • Provide a range of roles that couple power with

responsibility • Facilitate member-created subgroups

Guidelines for Online Communities:

Sociability Web Usability

Preece (2000)

• Purpose (clear definition)

• People (access, riles and effective communication)

• Policies (registration, governance, trust and security)

• Navigation • Access • Information design • Communications software • Finding people & Information • Ensuring readability of

instructions • Providing tools to support

moderators and other role-players

Design Principles for e-Learning Communities: Pedagogical Level Operational Level

Lambropoulos (2006)

• Intention • Information • Interactivity • Real-time evaluation • Visibility • Control • Support

It appears that most principles for online and e-learning communities are related

to community management and targeted to promote group coherence and

resolve differences as well as supporting members’ individuality. The e-learning

community guidelines for synthesizing pedagogy, community management, and

socio-technical design were suggested by the writer (Lambropoulos, 2006).

Other more informal principles to support teachers’ e-learning stressed the need

for a socio-cultural basis and came from the teachers’ community TappedIn®;

Gray and Koch (n.d.) suggested that the use of familiar settings, support of social

facilitation, and allowing flexible grouping supports e-learning communities.

Design factors for collaborative e-learning communities appear to be complex

and interrelated.

Kim (2001) suggested that there is no single answer for developing principles for

e-learning communities. However, one solution may be that the principles should

be open and agile enough so to be incorporated in any situated e-learning

interface design.

2.5.1.2. E-Learning Tools & Interface Design

Two types of interfaces were found in the literature, information provision

and groupware. Information provision interfaces dominate the field and tend to be

more data-centric and context-independent. They often deal with issues of

search and retrieval, information presentation, and visualisation. This is because

contextual information and socially relevant representations were rarely used

outside the lab (Hoadley, 1999; Faulkner, 2000). Shneiderman and Maes (1997)

suggested that learning management systems needed to overlap both types.

There are no indications that e-learning interfaces have been developed to

support both types to a great extend.

E-learning communities’ context derives from monological and dialogical

sequences so current tools that are directed to simply facilitate these processes

are mostly characterised as information-centric media. Hoadley and Enyedy

(1999; 2006) criticized such tools as computer-supported intentional learning

(Scardamalia & Bereiter, 1991), SpeakEsay (Hoadley, His & Berman, 1995), and

SenseMaker (Bell, 1998). They said that a chasm between internalisation and

externalisation in monological and dialogical sequences was reflected in the

interface. The challenge was to build tools that could help the learner to bridge

the “middle space”. Because monologue derived from dialogue as reflective

thought, there was a need to make this structure visible. Thus, visible dialogic

interactions could allow the interlocutors to give each other feedback leading to a

gradual refinement of partial meanings and construction of increasingly

sophisticated approximations of concepts. Therefore, tools need to fill out the

“middle spaces” of the continuum, that is the transitions for inclusion and

centralisation, reflections and interactions, topical and discursive coherence, and

the trade off between convergence and divergence (such as reaching a

consensus). They proposed the initiate-respond-evaluate (IRE) scheme used in

computer-supported collaborative learning argumentation and has reported both

positive and negative results (e.g. Siegel et al., 2001, Mercer and Wegerif, 1999).

Their IRE model was criticised for restricting creativity because of its limited three

levels scheme that did not allow critical thinking (Nassaji & Wells, 2000). (For a

review on a state of art technology for supporting collaborative learning see

Jermann et al., 2001.)

By studying such initial attempts, the problem appears to be related to a creative

interplay between collaborative learning theory and its translation into tools to

support collaborative leaning in a social and contextual basis. This was

discussed by Scardamalia and colleagues (1996) and Jonassen (n.d.).

Scardamalia and colleagues worked on knowledge databases so learners’

knowledge could be objectified, represented in an overt form, and then

evaluated, examined for gaps and inadequacies, added to, revised, and

reformulated (1996:201). Jonassen’s constructivist learning environments include

tools like listservs, electronic mail, bulletin boards, MUDs (multi-user

dimensions), and MOOs (MUDs Objected Oriented, like MediaMoo). Active and

constructive participation in learning proved to be essential but did not happen

naturally.

2.5.2. Tools to Support E-Learning

Communities

It appears that there are two kinds of tools to support human-human and

human-computer interactions: tools for observing and tools for analysing

interactions, divided in three categories, social/cognitive, cognitive/metacognitive,

and task/communicative (Figure 2.5.2-1):

Figure 2.5.2-1: Categorisation of collaborative learning tools

Collaborative Learning Tools

(Dillenbourg et al., 1996)

Observing

Interactions

Analysing

Interactions

social/cognitiv

cognitive/metacognitiv

task/communicativ

Observing social interactions were the first step built on a learner-generated

dialogical context for showing presence and co-presence to make the user

visible. As for analysing interactions, tools could capture the collaborative

learning cognitive and metacognitive distinction, for example exploring and

verifying solutions as well as the discrimination between task and

communication. The latter is referred to as dialogue management and

conversation models drawing from linguistics (for example, argumentation,

speech types, managing turn taking or making relevant contributions). The

following section presents existing tools that fit with the collaborative e-learning

dialogue scheme.

2.5.2.1. Tools to Structure Dialogical Sequences

The initiate-respond-evaluate (IRE) scheme (Hoadley & Enyedy, 1999)

triggered efforts on studies to support collaborative learning dialogical sequences

by predicting the forms of desirable dialogue as well as interactivity mechanisms.

Thus, it formed a basis for the design of computational models. Jonassen (n.d.)

introduced instructional activities for an interplay between learning and instruction

(Table 2.5.2.1-1):

Table 2.5.2.1-1: Learning and Instructional Activities

Learning Activities Instructional Activities Exploration Modelling Articulation Coaching Reflection Scaffolding

Jonassen said that each attribute should represent an instructional activity. There

were different tools supporting collaborative learning discourse such as the

collaborative notebook (O’Neil & Gomez, 1994) or the knowledge integration

environment (Bell, Davis & Linn, 1995) based on utterances as particular kinds of

speech acts (initiate, continue, repair and acknowledge), sentence openers and

floor control (I agree, Could you explain etc) (Traum, 1994). Another approach

that will be explored in detail in the next chapter was introduced by Mercer (1995)

and Wegerif and colleagues (1998); the authors worked on a collaborative

learning model for disputational, cumulative, and exploratory talk. Baker (2000)

suggested that what was required for tools to structure dialogical sequences was

relations between theory, model and corpus (i.e. transcriptions of interactions

data), and then design legitimate objects. Two examples of such models

translated into collaborative e-learning tools were InterLock and Messageforum.

InterLock was the by-product of McAlister’s PhD project Academic Talk (2004)

(http://learning.north.londonmet.ac.uk/ltri/academictalk/). As with AcademicTalk,

InterLock, worked on the same attributes to support collaborative e-learning

argumentation (http://www.interloc.org/; last accessed 21/12/2006), and Mercer

and Wegerif, participated in the new project (e.g. Ravenscroft, Wegerif, Mercer &

Hartley, 2006). InterLock viewed collaborative e-learning argumentation as a

game that promoted engagement and learning (Figure 2.5.2.1-1):

Figure 2.5.2.1-1. InterLock Interface

Message openers remained one of InterLock key features

(http://www.interloc.org/about.htm). According to its developers, the message

openers promoted coherent dialogue, thinking and deep learning which aids in

reusable and adaptable learning activity and dialogue game templates. However,

InterLock: (a) was too complicated for most users; (b) restricted creativity;

learners had to think in frames because they were obliged to use the tool and this

interrupted the discussion resulting in lack of context depth in reasoning; (c) the

attributes were distributed on the interface, so the structure of the conversation

restricted visibility of dialogical sequences overview; (d) there is no indication that

it promoted group-knowledge building; and (e) Java programming cannot be

easily integrated in wide use learning management systems; however, this was

not intended by the developers.

The next example had a more flexible nature and structured collaborative e-

learning in discussion forums. MessageForum was built by Jeong (2005) about

the same time as InterLock (2006) to support computer-supported collaborative

argumentation. Jeong suggested that online dialogical argumentation lacked

depth and was redundant. To solve these problems he created the

ForumManager, a tool to support collaborative e-learning argumentation based

on Toulmin (1958). The ForumManager was an MS Excel application for

downloading and analyzing messages (and message texts) in Blackboard

threaded discussion forums using Internet Explorer browser. This discussion

analysis tool created reports in Excel including reports on social interactions built

on social network analysis, that is visualisation of e-learners’ interactions. Table

2.5.2.1-2 describes the collaborative e-learning attributes in detail using symbols

and attributes rather than message openers:

Table 2.5.2.1-2. MessageForum Collaborative Learning Attributes

MessageForum Collaborative Learning Attributes

Symbol Description of symbol

+ Identifies a message posted by a student assigned to the team supporting the given claim/statement

- Identifies a message posted by a student assigned to the team opposing the given claim/statement

Identifies a message that presents one and only one argument or reason for using or not using chats (instead of threaded discussion forums). Number each posted argument by counting the number of arguments already presented by your team. Sub-arguments need not be numbered. ARG = "argument".

EXPL Identifies a reply/message that provides additional support, explanation, clarification, elaboration of an argument or challenge.

BUT Identifies a reply/message that questions or challenges the merits, logic, relevancy, validity, accuracy or plausibility of a presented argument (ARG) or challenge (BUT).

EVID Identifies a reply/message that provides proof or evidence to establish the validity of an argument or challenge.

The translation of the above model in a tool is depicted next (Figure 2.5.2.1-2):

Figure 2.5.2.1-2. MessageForum Attributes in a Discussion Topic

As Dillenbourg and colleagues had predicted in 1996, Jeong found that the

visibility of the structure helped learners’ reflection; more replies were elaborated

on previous ideas; there were greater gains in knowledge acquisition; there were

fewer unsupported claims, greater knowledge of argumentation processes; there

was no difference in knowledge acquisition, application of domain content, and

convergence towards consensus; and lastly, there were fewer challenges per

argument. The findings about the effects of using message constraints and

message labelling were similar to studies on other projects such as

ShadowPDForum (Jonassen & Ramirez 2005); NegotiationTool (Beers, 2004);

Future Learning Environment 3 (FLE3) (Leinonen et al., 2003); and Computer-

Supported Collaborative Learning Environment (CSILE) (Scardamalia et al.,

1994).

According to Jeong, the tool supported the visibility of the mechanisms that

facilitated three main areas: the strategic uses of message labels; the potential

group performance problems associated with personality traits; and methods and

tools used with message labelling to diagnose problems. Lastly, one of Jeong’s

recommendations for future research was to integrate tools in the forums for real-

time feedback to optimize group performance. One of the consequences of not

having the results in real-time is lack of situated social presence. Jeong has

presented similar results from other studies (e.g. Jeong & Davidson-Shivers,

2006; Jeong, 2008). Jeong’s tool also produced social network analysis (SNA)

graphs (sociogrammes) via Microsoft Excel (not in real time). Since SNA tools

appeared in online community research after 2000, it seems that Dillenbourg and

colleagues (1996) may have predicted another e-learning trend. The similarities

and differences between InterLock and ForumManager were (Table 2.5.2.1-3):

Table 2.5.2.1-3. Similarities and differences between MessageForum & InterLock

MessageForum VS InterLock + n/a Initial information - n/a Agree ARG = Question ARG = Challenge BUT = Reason EXPL = Reason

EVID / Maintain

The differences as regards the interface are mainly based on the different ways

in which the implementation of the main concepts have been carried out.

InterLock is a system whereas MessageForum is a tool incorporated in e-

learning systems such as Blackboard. The differences were connected to

interface usability as well as the visibility of attributes structure. Overall, it

appears that any tools to support collaborative e-learning need to aid:

• observing and analysing human-human and human-computer

interactions;

• evaluation to be close to decision making and preferably in real-time;

• flexible attributes to allow space for creativity;

• visibility of the communicative actions (interactions); and

• implementation in wide use leaning management systems.

The question that arises is whether conceptual frameworks can aid the design

process. This will be discussed next.

2.6 PROPOSITIONS FOR DESIGN

Based on the literature review, there are three propositions for design, the

Collaborative e-Learning Episodes, the Participation Levels, and the Sense of the

e-Learning Community Index.

2.6.1 Collaborative E-Learning Episodes

The dialogical context differentiated collaborative learning dialogue from

other “simple” dialogues, providing a distinction between mere information and

knowledge acquisition. Thus, collaborative learning appears to be the answer to

the initial question on quality in e-learning as these dialogical sequences promote

learning. A collaborative e-learning model is process-based and can be identified

in a dialogical context. Such a framework was found as a “knowledge sharing

episode” (Soller et al, 2002). A knowledge sharing episode was initiated when

there was new information, and ended with new knowledge construction.

A dialogical sequence for collaborative learning can be an episode; hereafter

called a collaborative e-learning episode (CeLE4). A CeLE is a communicative

discussion episode that has to have a starting point, a transition and an end point

that indicates a collaborative e-learning cycle. Based on Gumperz (1982:328-9)

for identifying the end point or point for CeLE completion, a CeLE inference is

involved in a complex series of judgments, including relational or contextual

assessments on how items of information are to be integrated into what we know

to expand our knowledge. These end points are defined by silence or mutual

agreement when an idea arises, which is new to some participants. The basic

interaction variables (attributes) can indicate collaborative learning value and

reflect pedagogical values in one CeLE. A numerical measurement was also

considered; however, all attributes function as inputs in a CeLE and are of equal

importance. In addition, the scheme needs to be flexible, not imposed and easy

to use. So the proposed process of one CeLE in accordance to its pedagogical

values is:

4 Examples of CELEs can be found on Appendix A_VII_13 and Appendix X.

1. Information-based as one way of communication;

2. Interactional as two ways communication (Explain, Question);

3. Collaborative Learning – Exploration (Explore, Reflection); and

4. Evaluation / Feedback.

This process of progressive dialogue can be depicted as follows (Figure 2.6.1-1):

Figure 2.6.1-1. The Collaborative E-learning Episode (CeLE)

The CeLE is proposed to indicate the collaborative e-learning levels, and as such

its value in real-time. This means that all e-learning participants can instantly be

aware of the level and the value of participation, as soon as the learner describes

the conversation act in an accurate way. Secondly, CeLE can identify the actors

and the modes of preferred participation. Lastly, CeLE, in combination with other

tools, can support the e-learning community’s socio-dynamics, that is the type of

interactions that can foster the community’s creativity. So if a CeLE can be

translated into a tool it will support observing and analysing collaborative e-

learning interactions as it:

• makes e-learners aware of active participation prerequisites;

• raises awareness of possibilities in collaborative dialogue and

argumentation;

• structures data in collaborative e-learning;

• measures the collaborative e-learning value;

• identifies e-learners’ type and thus posting value and quality;

• provides an overall view of the collaborative e-learning process; and

• facilitates proactive decision making.

Explain

Evaluate

Inform

Explore

Question

Interaction Pedagogical Value

Inform Suggestion Explain Elaboration

Question Reflection Explore Elaboration Evaluate Reflection

If CeLE can provide the attributes to observe and analyse interactions in

collaborative learning, then measurement, observation and analysis of

participation may be feasible. In an effort to measure the collaborative e-learning

value, Wiley (2002) suggested a qualitative classification built on a mathematical

approach. Evaluating participation in multi-thread discussion was conducted by

calculating an adjusted mean reply depth (d value) for each participant; the value

in the depth of discussion was considered on three levels:

1. 0 to 0.3 Monologue or lecture; no discussion

2. 0.3 to 1.2 Simple Q & A; chit-chat

3. 1.2 and higher Discussion, Multilogue

This is an interesting way to calculate value based on internal (monologue) or

external levels of discussion (dialogue); however, specific prerequisites and

attributes were missing. Acknowledging this limitation, Wiley’s reply depth or

thread depth will be used to calculate the level of persistence to a topic as

discussion depth.

Other than evaluating online messages as CeLE, participation is of major

importance in the search for quality in collaborative e-learning discussions. So a

proposition for measuring e-learners’ participation levels is presented next.

2.6.2 Levels of Participation

The Greek teachers’ passive participation is a normal and legitimate

behaviour and it is not a barrier to developing a sense of belonging. The literature

review increased understanding on passive and active participation but it did not

provide distinct and practical assessment. Recent approaches for measuring

participation levels are not designed to be automated (Table 2.6.2-1):

Table 2.6.2-1. Levels of participation measurement

Authors Levels of Participation

Beaudoin (2002) No Low

Taylor (2002) Lurkers Shirkers Workers

Oriogun (2006) No Low Medium High

Beaudoin suggested a distinction between low and no visibility learners; Taylor

proposed a classification between three groups, the workers or active

participants; the lurkers, who participated occasionally but mostly in a read-only

mode; and shirkers, the ones, that followed the minimum requirements. Oriogun

considered low, medium and high levels of engagement.

To automate a practical measurement of participation, the bell curve (Herrnstein

& Murray, 1994) is proposed for calculation on the basis of the total number of

messages sent in a forum (Table 2.6.2-2):

Table 2.6.2-2. Levels of activity measurement

Levels of Activity Measurement on the overall messages

X Sense of Community 4 High 76-100% 3 Medium 26-75% 2 Low 1-25% 1 Zero

Based on this measurement, a centripetal process, the participation eye, targets

to the sense of belonging to the community (Figure 2.6.2-1):

Figure 2.6.2-1. Participation Levels in Collaborative e-Learning Communities

The above levels show the symmetry/asymmetry in participation and also depict

the grey zone between passive and active participation characterised by the

sleeper effect; the latter is the white area where the participants decide to make

the first step, make the least collaborative effort. Furthermore, there is an area

outside the taxonomy and in the middle of the participation eye that refers to the

sense of belonging to the community and does not depend on active

participation. Active participation is initiated with the very first message and has

three levels, low, medium and high. If these levels can be displayed in real-time

on a discussion topic level and a course level, then participants in e-learning will

be able to be proactive by managing and evaluating participation in real time.

Real time online community management and evaluation of participation

provides immediate information delivery as needed for all stakeholders. It is cost-

effective; it is iterative rather than one-off as results are concentrated on the

process; it minimizes risk as decision making depends on facts rather than

assumptions; it is a catalyst for the stakeholders to accomplish their goals faster.

2.6.3 The Sense of E-Learning Community Index

Studying the Greek teachers’ participation in collaborative e-learning

communities suggested two ways to measure success and quality in e-learning,

the collaborative e-learning episodes (CeLE), and the sense of community. At the

first stages of this research, part of collaborative learning evaluation was initially

anchored in empathy to provide a sense of belonging. Based on the framework

suggested by Levenson and Ruef (1992:234), the participants in the initial study

had to answer questions on: (a) knowing what another person was feeling when

reading the message; (b) feeling what another person was feeling when reading

the message; (c) whether they took any action; and (d) whether the tools helped.

It is important to note that incorporating these attributes in a questionnaire was

found the only way to acquire results as all information in online discussions is

textual.

However, the measurement based on empathy was found inadequate to

evaluate the sense of community; the only tangible outcome was that the

members who were found to develop empathy were the ones who were very

active in the community (Lambropoulos, 2005c). This result does not describe

the sense of belonging and its interrelated attributes in a coherent way. So a

second approach was developed, the Sense of e-Learning Community Index

(SeLCI) and empathy was one attribute of the new framework. This process will

be further elaborated in the research design in Chapter 5.

The question here is on suitable research methodologies to inform design

towards the development of tools and evaluation techniques for collaborative e-

learning communities. This will be explored in the next chapter.

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Tools and Evaluation Techniques for Collaborative E-Learning Communities Chapter 3: Research Design

The Research Design: Research Methods for Investigating Collaborative E-Learning

Communities

• E-Learning research advantages and limitations

• The need for a systematic e-research design to examine the research context

• Why and how ethnotechnology can support investigation in collaborative e-learning communities

• The dual nature of human-human and human-computer interaction methodologies

• The research coordination and design

Chapter 3 introduces the research design. A review of research methods to support

design and e-learning shows advantages and limitations caused by their

multidisciplinary nature. Ethnotechnology was found to be a suitable approach to

examine the research context as well as to analyse human-human and human-

computer interactions in e-learning environments. The questionnaire design, time

series design and research constraints are presented.

3.1. INTRODUCTION

Rapid technological changes influence communication, collaboration,

information and knowledge management for e-learning. Within the context of these

new challenges, research design needs to explore human-human and human-

computer interactions which have learning as their purpose, that is Human-Computer

Interaction Education.

Sasse, referring to the different aspects of the HCI nature, says that “the lack of a

single agreed research strategy discipline leaves an individual researcher planning a

specific research undertaking out on a limb” (n.d.). This multifaceted nature is

reflected in the lack of a single agreed strategy; however, this disadvantage can be

tackled by triangulation. Nonetheless, there is a risk; some times an amalgamation of

different research methods fails because of the disengagement between methods

and their underlying methodology (Boehner et al., 2007).

This chapter builds on situated e-research. The first section discusses issues for e-

learning research and ethics. Then, it employs an aspect of ethnography, that is

ethnotechnology, to examine the research context. Ethnotechnology is used

alongside human-computer and human-human interaction analysis to shed more

light on collaborative e-learning communities by triangulating sides of space and

time. Time-series design is suggested as a means of coordinating e-research.

3.1.1. E-Learning Research

E-Research employs web server analysis, application logs, data mining,

participant research, virtual ethnography, and Internet use. Because of its virtual and

interdisciplinary nature, e-research challenges research methods, e-researcher’s

skills, and ethics (Anderson & Kanuka, 2003). According to the British Psychological

Society (http://www.bps.org.uk/, n.d.), the ethical principles for conducting research

with human participants include general principles that may differ in e-research.

Anderson & Kanuka said that creating and maintaining respectful relationships with

e-participants is underpinned by three principles: voluntary informed consent;

privacy, confidentiality and anonymity; and recognising the elements of e-research

risk. E-researchers need to balance the conflicts which derive from the

implementation of these principles. For example, a hacker hacked the server where

the final study was hosted and wiped out all database tables; on a second occasion,

at the researcher’s request, the system operators collected data including

demographic details for GSN’s own use and also for research purposes.

On the other hand, Robinson and colleagues (2007) suggest that a combination of

methods is needed, but in order to avoid any form of control over the participants,

data can be collected as it occurs naturally. To Robinson and colleagues, working on

ethnographically-informed empirical studies, it is legitimate to consider such data in

order to understand practice in its own terms. This approach may resolve the

problem in research created by the Hawthorn effect. However, in reality “there are no

clearly defined criteria for appropriate ethical behaviour for all researchers or all

research activity” (Anderson & Kanuka, 2003:58).

In order to address the ethical issues, this study was approved by three different

organisations: the London South Bank University Ethics Committee, the Greek

Pedagogical Institute, and the Innovations Office, part of the Greek Ministry of

Education and Religious Affairs. Prior to the transfer of this research to LSBU there

had been no approval sought for the two initial studies not presented in this thesis.

Nonetheless, these were conducted under all ethical considerations and principles

and participants’ consent was obtained for all studies. The consent was obtained by

the participants’ signature on a pro-forma which emphasised that they could withdraw

from the study at any time without providing any explanation. The participants were

allowed to keep a copy; in addition, the right to withdraw was stressed in the user

policy (netiquette) available online as well as sent to the participants prior to the

study.

3.2. RESEARCH DESIGN

The proposed research design is (Table 3.2-1):

Table 3.2-1. Research Design

RESEARCH DESIGN Target Use

Research Methodologies Coordination Implications

for Design Evaluation

1 HCI-HHI Ethnotechnology √ √ √ 2 Qualitative Methodologies HHI A Message analysis √ 3 HHI Social network analysis √ 4 Quantitative Methodologies HCI-HHI A Questionnaires √ √ HCI B Log Analysis √ √ 5 n/a Time-series design √

The research design targets methodological triangulation, that is the application and

combination of several research methodologies of the same phenomenon to

corroborate one set of findings with another; the hope is that two or more sets of

findings will converge on a single proposition (for a review of triangulation, see

Massey, 1999). Initially, ethnotechnology can increase understanding of the research

context for human-human and human-computer interactions (HHI & HCI).

In addition, time-series design coordinates the research activities on a temporal basis

for baselines and interventions. These approaches will be analysed in this chapter as

regards their scope, principles, and research instruments as well as their advantages

and disadvantages for this particular study.

3.2.1. Examining the Research Context

For the purpose of this study, the examination of research design should

scrutinise the situation as regards participation in collaborative e-learning

communities and determine implications for designing successful collaborative e-

learning communities. Ethnographic research was found to represent a long tradition

of studying social processes in real life situations, used to uncover the knowledge,

ideas, beliefs, values, and purposes of systems use, and thus informing the

designers about the setting. It has been exploited in computing research, especially

after Suchman (1987) discussed the profound mismatch between the generic models

of work on which IT systems are built at the time and the actual nature of work in

which they are used.

Ethnography is located in the field of naturalistic research (qualitative), distinguishing

it from positivist research (quantitative). It involves the ethnographer immersing

herself in people’s daily life for an extended period of time, watching what happens,

listening to what is said, asking questions, and collecting whatever data is available.

It is an ongoing attempt to place specific encounters, events, and understandings into

a more meaningful context. It is not simply the production of new information or

research data, but rather the way in which such data are transformed into a written or

visual form (Tedlock, 2000:455).

The advantages of ethnography in the investigation of tools and evaluation

techniques for collaborative e-learning communities are related to the rich description

of the research context and the exploratory stance that relies on the researcher’s

own ability to provide rich descriptions of data and understand the meaning of social

situations. However, the ethnographer’s role towards a rich fieldwork is also a

disadvantage. Many ethnographers advocate the need for a trained ethnographer in

order to go beyond simple descriptions (fieldwork), to a genuine analytic one (scenic

fieldwork) (McGarry, 2005:67; Ian Sommerville, Professor of Software Engineering at

Lancaster University; personal communication via email, 01/05/2007). This has

created two approaches in the use of ethnography in systems design, one that

suggests there should be two groups of experts, the engineers and ethnographers,

and the second that sees the engineer conducting the fieldwork. After stressing the

importance attached to the use of ethnography for fieldwork analysis in design, two

examples from these traditions will be presented.

3.2.1.1. Ethnography

Ethnography was suggested as the preferred approach to study lurkers and

thus, participation in online communities (Nonnecke, 2000). One way to utilise

ethnography in design is by ethnography’s scenic fieldwork, that is descriptive and

historical accounts for understanding social settings. These provide the explanatory

frame and the narrative explaining of “why” and “how” these implications one arrived

at. This is a demanding process, so some systems designers employed

ethnographers to provide description of the context needed for design. However,

there was a problem related to finding common ground and communication channels

for both the fieldworker and the engineer. Despite the efforts to ease their differences

(e.g. Hughes et al., 1997), and after almost 10 years of research, Hughes (1999)

concluded that there are major differences between ethnography and systems

design; they are two different mentalities.

A more recent approach considers that an engineer is able to conduct the fieldwork

herself. Although this approach has created questions on the engineer’s

epistemological validity there were successful implementations (Furnis, 2004; Sharp

et al., 2006). Studying teamwork in their own agile software development groups,

Sharp and colleagues (e.g. 2005, 2006) adopted ethnographic perspectives in order

to put design to work in particular contexts, adopted and adapted by people in the

course of practice, contradicting the definition of the “user” as a passive recipient of

technology. Thus, design is the active process of incorporation and co-evolution of

technologies, practices, and settings.

Assumptions on the use of ethnography for the ethnographer’s role as well as the

locus of e-research were revisited. If the designer/researcher is located within their

domain of study, in this case her own community of practice, can immerse herself

easily since the prolonged engagement and immersion in the context required in

ethnography already exists. Thus, she can progressively reconfigure new ways to

understand ‘users’ and ‘user contexts’ by understanding work practices within her

own culture and society as inspirations and foundations for design activity in order to

support new ways of working. These were the assumptions that were used in this

study.

3.2.1.2. Ethnotechnology: the Virtual Ethnography

Ethnography employed in real environments has taken advantage of

conversations, written materials, and observation. In fact, Button (2000) suggested

that it is important to consider how relevant people do what they do, that is the

‘interactional what' of their activities. This is the explication of members' prior

knowledge: what people have to know to do work, and how that knowledge is

deployed in the ordering and organisation of work. He proposed that this

consideration provides the key to understanding the contribution of sociology to

engineering and design.

Ethnotechnology, has been only recently used to shape a strategy in computing and

e-learning research as in collaborative e-learning (Guribye & Wasson, 2002; Guribye,

2005) and online Communities of Practice (CoP) (Paiva, 2005; Talamo, 2005;

Talamo & Ligorio, 2002). It is a specific field for studying the impact of technology

raised from the observation of a mismatch among the users’ way of tools’

implementation and the functions for which the developers had planned them

(Grossen et al., 2006). Ethnotechnology has been recently employed for developing,

animating, and analysing online CoP in the ITCOLE EU project (Talamo, 2005;

Talamo & Ligorio, 2002). The project aimed at the creation of software tools,

pedagogical best-practices, and testing, based on cycles of software development.

Talamo and Ligorio combined ethnotechnology and discourse analysis in

synchronous and asynchronous communication within the ITCOLE CSCL system,

built to support collaborative e-learning communities. Following Talamo,

ethnotechnology can be supported by textual analysis and can rely on

ethnotechnologist’s empathic understanding of her context, abandoning her

preconceptions, and treating everything as ‘strange’. Full participation is feasible

when she is fully engaged as when they belong to a CoP, however, her research role

is partly covert.

The research issues are similar to ethnography, such as the role of the researcher

and lack of generalisability since ethnographic approaches are always in principle

incomplete (Hine, 2005).

3.2.1.3. Ethnotechnological Methods

The GSN Deputy Director, Michael Paraskevas, said that the Greek teachers

were not using the tools provided. His observation brings forward one of the primary

aims of ethnotechnology, studying the impact of technology raised from the

observation of a mismatch among the users’ way of tools’ implementation and the

functions for which the developers had planned them. Conducting scenic fieldwork

within the Greek Community of Practice (CoP) appears to have both a real and

virtual locus. Participant observation in activities such as seminars and conferences,

talking to colleagues, and conducting interviews with individuals from the Greek

educational authorities can reveal some aspects of the problem of participation in

collaborative e-learning communities. As for the online environment, focus groups as

well as the quantitative human-computer (logging) and qualitative human-human

interaction analysis (messages analysis) can shed more light in understanding the

Greek e-learners. Thus ethnotechnology can be utilised in e-learning design.

Focus groups, widely used in Human-Computer Interaction (e.g. Faulkner, 2000), are

compatible with ethnography and thus ethnotechnology. Suter (2000) worked on the

dilemma of their use in ethnography and provided three reasons they should be

seriously considered as an alternative way for generating data: (a) access to

participants' interaction on topics that are either difficult to observe or rare in

occurrence; (b) a focus group improves ethnographic practice by providing another

option for generating appropriate data; and (c) the method raises important questions

of relevance between focus groups and participant observation. Provided that the

participants in a focus group discuss the topic of their specialisation and interest, a

focus group can provide insights in hidden aspects of design with data that could not

be acquired otherwise. So in this study, one focus group is used to reveal best

practices and tools for activating the passive participants and a second to evaluate

the tools and evaluation techniques before their implementation.

Ethnotechnological research conducted in e-learning environments can acquire

information about the users by tracing them. A log, also referred to as web-log,

server log or log-file, is usually in the form of a text file and is used to track users’

interactions with the computer system they are using. Examples of what information

can be collected include (Laghos & Zaphiris, 2006): when people visited a site; the

areas they navigated; the length of the visit; frequency of visits; patterns of

navigation; where they are connected from; or details of the computer they are using.

A typical logging operation consists of collecting messages and then performing

analysis, frequently by counting and/or sorting using various criteria (Nonnecke,

2000:21-22). The advantages are attractive (Nonnecke, 2000; Preece et al., 2002;

Laghos & Zaphiris, 2006): log files can be automated; are time stamped; are useful

for finding usage/activity patterns; can study users’ behaviour; provide opportunities

of quantitative analysis and further research. The disadvantages include the need for

power tools for large amounts of data; permission to conduct the research which is a

bureaucratic process in governmental organisations; privacy issues are raised; and

there may be inadequacy in answering questions such as “why” and “how”. In this

study, logging can offer information on the Greek teachers’ passive participation in

Moodle@GSN. Such information can be translated to:

a. the number of passive and active participants;

b. passive participation levels measured by time spent on the system,

c. the depth of discussion threads to measure interactivity; and

d. tool usage.

Logging can also offer opportunities for correlations in order to identify practices that

work better than others.

However, there are some disadvantages. Considering everything as data suggests a

data overload and thus, there should be analytical frameworks in place to facilitate

transitioning from ethnographic inputs to designing concepts (Jones, 2006). Existing

analytical frameworks build on ethnographic inputs to provide designers with a series

of tools and techniques for understanding social settings and organizing their

observations to derive models for design (e.g. Contextual Inquiry, Beyer & Holtzblatt,

1999; DiCoT, Furniss, 2004). Another problem is the danger of amateurisation of

ethnography in practice because fieldwork itself is only the first step; the analytical

treatment of that data determines whether it is fieldwork or scenic fieldwork

(McGarry, 2005:68). Reservation exists on the Greek teachers’ passive participation

in Moodle@GSN; if there is no active participation, there is no narrative, that is zero

history. But e-learners do leave traces that appear in the log files. The key variance

of passive participation may not be the cause and this can be detected.

So ethnotechnology can be incorporated in e-learning engineering building on scenic

fieldwork, implications for design, and ethnographic inputs.

ETHNOTECHNOLOGY

Thematic Analysis Messages

(qualitative data)

Social Network Analysis Interactions

(quantitative data)

Questionnaires Open & closed questions

(qualitative & quantitative data)

LoggingLog files

(quantitative data)

Fieldwork observation, interviews

(qualitative data)

Figure 3.2.1.3-1 Ethnotechnology and methods

3.2.2. In the Search of Quality: Human-Human

Interaction Analysis

Human-human interaction analysis employs thematic analysis and Social

Network Analysis so as to improve understanding of e-learning interactions quality.

3.2.2.1. Posts: Thematic Analysis

Analysis of the posted messages could provide information about active

participation and the quality of the Greek teachers’ communication and learning.

Theory and prior-research driven thematic analysis for collaborative learning (see

MA dissertation, 2002) was used for code development. This is a process for

encoding qualitative information in order to relate the data to prior ideas (Boyatzis,

1998: 99-127; Braun & Clarke, 2006). Coding needs to be ‘usable’ from other

researches for a high inter-rater reliability level; simple to understand and remember;

relevant to the context; allow quantitative analysis; and use of a wide variety of

information. Codes had been developed in a continuum following a cyclic process of

sampling, developing themes and codes and validating and using the code scheme.

Themes and clusters for developing protocols were grouped based on a

developmental scale on cognitive complexity (Boyatzis, 1998:143). Furthermore,

statistical comparison could determine valid differences by reducing large amounts of

text into numerical data so as to be analysed statistically. Consequently, thematic

analysis has been used in posts analysis searching for Collaborative e-Learning

Episodes (CeLEs) as well as in open questions in the final questionnaire.

In this study, CeLE analytical framework was found to neglect significant information

related to social interactions; these were the social cues such as words at the

beginning and end of a message (e.g. greetings and sign offs) and emoticons. Thus

two more analytical frameworks were considered in order to increase understanding

of collaborative e-learning; Henri’s (1992) five dimensions for message analysis, and

Fahy and colleagues’ Transcript Analysis Tool (TAT) (2001, 2005). Her model

provided an initial framework for coding CMC discussions; however, it lacked

detailed criteria for systematic and robust classification of electronic discourse

(Howell-Richardson & Mellar, 1996). In addition, it has been criticised for poor

theoretical support and being strictly a teacher-centred instructional paradigm

(Gunawardena & Lowe, 1997). Despite these limitations, there is an advantage in

Henri’s proposition, which is the social cues coding for analysing social messages:

self-introduction, expression of feeling, greeting or emoticons for describing emotions

(Henri, 1991:126). After Henri, more researchers have attempted to analyze such

social effects of conferencing exchange (e.g. Rice & Love, 1987; Walther, 1996) or

sociability of online communities (Preece, 2000).

As a result, one CeLE was the unit of coding as the most basic meaningful segment.

The attributes of a CeLE were initially based on conceptual and empirical work;

however, inter-rater reliability had to be reached to ensure correct coding. Therefore,

an analysis of 25% of the data was conducted by an independent researcher in

Atlas-ti™ based on the CeLE codes without any prior discussion. This revealed an

initial reliability of 3% on the data which was clearly unacceptable. The classification

indicators were rewritten in a clearer and simpler way and a further 10% of the data

was coded giving a reliability of 50%. Then, the themes and clusters were discussed

and analysed with the independent researcher giving a reliability of 90% on a further

25% of the data. A second independent researcher verified the process with a

reliability of 93% on a 25% sample. Reliability in the 90%+ range was operationally

considered as being acceptable.

The schema has been also tested by 2 colleagues using messages from different

units of analysis from SKYPE and chats (Lambropoulos et al., 2008). It appeared that

social cues can be related to building social interactions prior to collaborative e-

learning and can be included in coding sub-units within initiation (Table 3.2.2.1-1):

Table 3.2.2.1-1. Collaborative e-Learning Episodes Codes Matrix

Collaborative e-Learning Episodes LEVELS OF ABSTRACTION

Level 3 Level 2 Level 1 CeLE Elements Analytical Corroboration Definitions Indicators for classification

0 Initiation & Social cues Initiations, additions or superficial amendments, repetitions, uncritical information, social cues, etc.

Information, statement, definition, emoticons, abbreviations, lexical items, quoting, images, audio etc

1 Question - Information Question, proposition, instruction, opinion, history of something, , etc

Recommendation, question, bullet points, I think, I believe, instruction, I know, have worked, I prefer.

2 Explanation Explanation and self-explanations, requirements, examples, summaries, etc

because, this is why, thus, therefore, example, further explanation, help, nice behaviour & suggestion.

3 Agreement Agreement, confirmation, corroboration, etc. It is very interesting, refer-to-a-name, same, Yes, I agree & you are right.

3a Disagreement Disagreement, difference, discrepancy, flaming, etc. but, however, on the contrary & different.

4 Exploration Hypothesis, comparison, example, argument, resource interdependence, critical information, competition of ideas, reasoning, argument, etc.

alternative, I have an idea, something else, what about, what do you mean, I tried if, might, could, would, should, think & suggestion.

5 Evaluation Comparison, assessment, best practice, etc. best, it is important, comparison, easiest, worst, unfortunately & having no meaning.

6 New ideas - Co-construction Strategy, plan, method, plan, procedure etc.. solution, summary, overall, we agreed &

finally.

Enhancing social cues required a specific community management framework. A

focus group provided a scheme for best community development practices and tools

to promote active participation.

Quantifying qualitative data was essential in thematic analysis. Other than counting

the words in a post as an indicator of text richness, two relevant concepts were found

in Fahy and colleagues’ research on their Transcript Analysis Tool (TAT) (2001,

2005), density and intensity. Density was the ratio of the actual number of

connections observed, to the total potential number of possible connections: Density

= 2a/N(N-1), where "a" was the number of observed interactions between

participants, and "N" was the total number of participants. The researchers stressed

that the measure of density is sensitive to the size of the network, so larger groups

will be likely to exhibit lower density ratios than will smaller groups.

Intensity in this study referred to the levels of participation and persistence where

persistence is the level to which participants pursue topics. Persistence was related

to interactivity and discussion depth operationalised by measuring the number of

levels of communication in a particular discussion thread from the first posting to the

last (depth of discussion threads).

Other than the posts’ quantitative and qualitative examination, investigations of social

interactions can shed more light in the research context and can triangulate the

findings with ethnotechnological fieldwork.

3.2.2.2. Interactions: Social Network Analysis

Social Network Analysis (SNA) was used to understand e-learning related to

the Greek teachers’ sense of belonging to the collaborative e-learning community.

SNA has been used to visualize communication and relationships between people

and/or groups through diagrams by depicting social relationships between a set of

actors (Baroudi, et al, 1986). The most widely used SNA attributes are nodes (the

actors of study), relations (the strands between actors), and centrality (central or

isolated person). SNA focuses on complete (or group) and ego networks; however,

only group analysis on cohesion and centrality was found suitable for this study. In

addition, several tools were considered for SNA as well as their integration in

discussion forums as to support co-presence.

Cohesion: Network density for group thickness, reciprocity, cliques, and structural

equivalence were used to measure the level of cohesion. Network density is the

proportion of possible links in network that actually exist; it was evaluated by the

adjacency connection reports. Sent-Received (S-R) number of messages is related

to participants’ reciprocity. More specifically, reciprocity is the number of ties that are

involved in reciprocal relations relative to the total number of actual ties (Hanneman

& Riddle, 2005). A clique is a set of actors with each being connected to each other

in smaller groups. Structural equivalence and in particular the CONCOR technique

(CONvergence of iterated CORrelations, White, Boorman, Breiger, 1976; Breiger et

al., 1975), describes the actors that have similar relations to others in the network

with dendrogrammes. So the degree to which two nodes are structurally equivalent

can be evaluated by measuring the degree to which their columns are identical:

Centrality: Group centrality (Everett, 2005; Freeman, 1979) refers to the distribution

of power between the community members and is measured by centrality, closeness

and betweenness. In this study it referred to the total number of Sent-Received

Messages (direct links), out-degree (replies made) and in-degree (received

messages) centrality. Group closeness is defined by the normalised inverse sum of

distances from the group to a node outside the group (Everett, 2005:61); in this study

closeness was related to reciprocal distances. Betweeness is the number of indirect

links in which the actor is required as an intermediary; this characterise the mediator

as the controller of the information flow in a network.

SNA Tools: SNA has been used for offline (e.g. Breiger, 2004; Bender-deMoll &

McFarland, n.d.), off-line and online (e.g. Wellman, 2001), and online educational

contexts (e.g. Daniel, 2007; Laghos & Zaphiris, in press). Presenting relationships

and perceiving solutions derived from visualisation can assist annotations,

consultancy or revision since data visualisation proved to be important for user locus

of awareness, control and initiative (Shneiderman, 2000). However, even though

SNA tools can depict the activity in online human-human interactions, the use of

these tools in educational contexts is offline. Offline SNA tools need the researcher to

input the data either based on observation (e.g. Petropoulou, 2006; Laghos &

Zaphiris, in press) or extract the data in a file such as excel files (Jeong, 2005).

These data are inserted to SNA software for visualisations graphs, however,

providing an out-of-date evaluation and decision making.

SNA tools could support e-learning discussions in real time. Kreijns and colleagues

(2002) have suggested that if a group awareness widget existed, a software tool

providing the learner group awareness about the others in the task and in the non-

task context can enhance groups’ sociability. Additionally, social presence and co-

presence can enhance the sense of community by providing a picture of the

community (Beer et al., 2005). Social presence was the degree by which a person

was perceived as real in an online conversation (Meyer, 2002:59). Real-time SNA

has started to support e-research; for example, Microsoft uses SNA tools to visualise

users’ clicks on web pages (Milic-Frayling, 2007). To date, some open source offline

SNA software used in discussion research are SoNIA (Stanford University; Bender-

deMoll & McFarland, 2006), Pajek (University of Ljubljana, Slovenia; Nooy et al.,

2005), UCINET (Analytictech, http://www.analytictech.com/download_products.htm)

and JUNG (Java Universal Network/Graph Framework, http://jung.sourceforge.net/).

JUNG was found to be compatible to Moodle and was integrated in Moodle for the

purposes of this study. Other than the SNA online use, an SNA software is essential

for data analysis. After studying comparisons between several SNA desktop

applications (Laghos, 2007; Huisman & van Duijin, 2005) UCINET (Borgatti et al.,

2002) was found most suitable for this study. The main reasons were its usability and

the support provided (Everett and Borgatti; personal communication via email,

September 2007).

Overall, fieldwork and thematic analysis provide the data for qualitative analysis that

can be quantified for statistical analysis; logging and Social Network Analysis provide

data for quantitative analysis and social networks visualisation. Open and closed

questions in a questionnaire could be used for triangulation so as to reveal whether

two or more sets of findings could converge in a single proposition.

3.2.3. Questionnaire Design

A questionnaire is a self-reporting technique whereby participants fill in the

answers to questions themselves; its purpose is to elicit facts about the respondents,

their behaviour and their beliefs/attitudes (Nielsen, 1993). According to Nielsen, there

are three types of questions: open-ended, closed, and scaled. Open-ended questions

give freedom to the participants to respond, closed, where the participants have to

choose from several choices, and scales where the respondents must answer on a

pre-determined scale. They have been used for: online communities (Andrews et al.,

2003); evaluation of the sense of community (e.g. Brook & Oliver, 2006; Daniel,

2007); revealing lurkers’ opinions (e.g. Nonnecke, 2000; Gulati, 2006); or evaluation

of evaluation tool’s effectiveness (e.g. Silius et al, 2003).

Advantages derived from methodology were: easy access to participants, especially

via emails or web-based questionnaires; use of qualitative or quantitative questions

or a mix; there can show differences over time. The disadvantages were related to:

an idealised version of information; lack of honest and accurate responses; very low

response rates from passive participants and less than 20% response from active

participants; and difficulty in having an immediate follow up (Mason, 1999). However,

these disadvantages can be eliminated if used in conjunction with other

methodologies. The questionnaires stages and objectives are (Zaharias, 2004;

Kirakowski and Corbett, 1990) (Figure 3.2.3-1):

Figure 3.2.3-1. Questionnaire Design Methodology

Three questionnaires were given to the participants, at the beginning, in the middle

and in the end of study. The first questionnaire was used to acquire information on

demographics, conditions of working and learning on the internet and initial

knowledge on collaboration. The second questionnaire was used for e-tutoring

purposes and it is not part of this study. The third questionnaire targeted to

triangulation via the evaluation of: community evolution, the sense of belonging,

empathy, trust, and knowledge acquisition. All questionnaires were given to 3-5

respondents in three phases in both English and Greek languages prior to the study.

Lastly, the final section presents the e-research design needed for the e-research

coordination.

3.2.4. E-Research Coordination: Time-Short Series

Design

Time-based coordination was used to capture the development and to

triangulate sides of space and time of the unit of analysis. The use of quasi

experimental time-short-series design was found a suitable approach to set a

timeframe (Shadish et al., 2002). Quasi-experimental design is not preferable to

other research design such as experimental design, but it is used when an

experiment is not feasible, most of the time due to the group selection criteria: the

groups were chosen and assigned out of convenience rather than randomization.

Most importantly, controlled environments are impossible where participants have

access from remote and distributed locations. Also, there is little loss of status or

prestige in doing a quasi-experiment instead of a true experiment.

Time settings refer to two main sets, defining the baseline(s), and time series.

Baseline refers to the observation of behaviour prior to any treatment designed to

alter behaviour. As such, the treatment effect is demonstrated by a discontinuity in

the pattern of pre-treatment and post-treatment responses. The groups which are

going to be used in this study are inactive. The latter suggests a solid baseline for

treatments and effects related to causal inference, not affected by threats like history,

natural development and maturity for studies mostly observed in children’s research.

In time-short-series design aggregation and causal inference are not necessarily

affected if a detailed amount of data could be collected. There are three dimensions

to be investigated in order to examine the nature of intervention: (a) the form of the

effect (the level, slop, variance and cyclicity); (b) its permanence (continuous or

discontinuous) and (c) its immediacy (immediate or delayed).

Two baselines are initially suggested, before treatments, community management

and use of new tools, and after treatments. The time series design is (Table 3.2.4-1):

Table 3.2.4-1. Observations, interventions and evaluation

INTERVENTION & EVALUATION Observation Course Day Community Management Tools

0 O0 Baseline 1 - days √ n/a 1 O1 1 √ n/a 2 O2 3 √ n/a 3 O3 7 √ n/a 4 O4 14 √ n/a 5 O5 21 √ n/a 6 O6 Baseline 2 √ √ 7 O7 28 √ √ 8 O8 End of the course √ √

The initial baseline describes the research context before any intervention. Then

community management and tools (treatments) support the e-learning community.

Limitations and strengths of time-short-series design in this study are (Sanson-

Fisher, 2004) (Table 3.2.4-2):

Table 3.2.4-2. Limitations and strengths in Time-Short Series

Time-short-series

Limitations Strengths

• Fewer study units limits generalisability

• Measures must be suitable for repeated use

• Depends upon successful, temporal relationship between intervention and measure

• Process-based framework creates close examination of both units and interventions as well as causal inference

• All units could get intervention if it is effective • New theories can be created • Flexibility related to individuals, small and large units • More intervention research and knowledge • Can examine each intervention component • Interdisciplinary Research exists • Clear research design and data analysis • Consisted with decision making processes

Time-short-series strengths add value to research, and limitations are considered as

similar to any other research; thus, provision of measures can ensure the validity and

reliability. Overall, time series design seems to have the potential to provide the

needed time-based coordination of measurements to provide implications for design

and e-learning evaluation.

The methodological approaches and their attributes are (Table 3.2.4-3):

Table 3.2.4-3. Research Methodology

ETHNOTECHNOLOGY DESCRIPTION

1 Fieldwork

1. Participation in projects, conferences, seminars, online discussions of Greek teachers’ associations and schools in Greece

2. Documentation, manuals and presentations by the Greek educational authorities

3. Personal opinions, conversations, and emails 4. Richness of text

2 Pre-Questionnaire 1. Demographics 2. Conditions of working and learning over the Internet 3. Initial knowledge on collaboration

3 Logging 1. Frequency of visits 2. Number of active and passive participants 3. Active participation levels 4. Passive participation levels

4 Thematic Analysis 1. Collaborative e-learning episodes analysis 2. Sense of e-Learning Community Index

• Number of Collaborative e-learning episodes

5 Social Network Analysis

2. Group Centrality • Centrality

6 Post-Questionnaire

1. Sense of e-Learning Community Index • Community evolution • Sense of belonging to the e-learning community • Empathy • Trust: knowledge exchange, help and support • Collaborative e-learning quality: participants’

opinions 2. Usage and usability of collaborative tools 3. Professional development

7 Statistical Analysis

1. Examination of the data, missing data, normality. 2. Descriptive Statistics: crosstabulation, frequencies,

arithmetic means, standard deviations, and exploration

3. Correlation: Pearson correlation coefficient (r). 4. Inferential statistics: statistical significance, p-value

(Cronbach's alpha, α), and null hypothesis.

8 Intervention Analysis 1. Form of the effect: the level, slop, variance and

cyclicity 2. Its permanence (continuous or discontinuous) 3. Its immediacy (immediate or delayed)

3.2.5. Research Constraints

There were several constraints for the study.

First, a number of constraints occurred because the research was conducted

completely over the Internet (e-research): data overload; time and knowledge

required to access, filter, sort, and combine the quantity of information produced, and

endless opportunities.

Secondly, additional constraints reflect the nature and circumstances under which

the research is carried out including the time frame, having one individual performing

all research functions and simultaneously being an active participant in the Greek

educational community, use of open source tools, not being an expert ethnographer,

and having limited programming skills.

Thirdly, there is also a need to acknowledge the Greek teachers’ passive

participation; the ratio on questionnaire response is anticipated to be less than 20%.

This is not only a phenomenon observed in the Greek teachers’ reality; Cuthell

(2005) reported limited activity in a 5 months project on MirandaNet, a British

teachers’ network similar to GSN. Another limitation is related to the target

population, which is not representative of the total population of the Greek teachers

but naturally occurred in the Computer-Mediated-Communication space.

Lastly, even though there are recent studies on participation in online communities,

there is no similar research for comparison in the Greek and international research

community.

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Tools & Evaluation Techniques for Collaborative E-Learning Communities Chapter 4: Research Context

The Research Context: Ethnotechnological inputs and preliminary studies

• Understanding the research context

• The Greek teachers’ background and characteristics

• The intentions of the Greek educational authorities

• The Greek School Network and the e-learning environment provided to the Greek teachers

Chapter 4 reveals aspects of the research context with the aid of ethnotechnology.

This is connected to the Greek educational authorities’ intentions, targets, and tools

provided for the Greek teachers’ professional training and development. One of the

tools was Moodle@GSN, the e-learning platform supported by the Greek School

Network. The chapter also sheds light to the Greek teachers’ needs, background,

and characteristics as well as their overall activity at Moodle@GSN.

4.1 INTRODUCTION

The main objectives of this chapter are:

• understanding the context from the Greek teachers’ viewpoint;

• finding best practices for communication and social interaction; and

• implications for design.

Because some parts of the jigsaw were not found in Greece, observant participation

in other groups was considered necessary. Thus the following projects were also

used to provide information:

1. the European projects “E-Tutor” (June 2006; http://www.etutorportal.net/) and

“e-learning fundamentals” (June 2007- http://fecone.passionforlearning.eu/);

2. the Greek English language teachers (PEKADE; http://pekade.gr);

3. the Greek association for the valorisation of ICT in education (EEEP;

http://www.eeep.gr);

4. the Greek teachers with a special interest in music (EEMAPE;

http://www.primarymusic.gr/);

5. the primary teachers’ training programme conducted by the Greek

Pedagogical Institute within the Greek schools (September 2006).; and

6. participation in several conferences with publications in collaboration with

other Greek teachers.

Access was provided by the researcher’s colleagues and there were discussions with

the organisations’ directors as well as members.

4.1.1. The Native’s Point of View, background and

characteristics

The participants in e-learning at Moodle@GSN were the directors, the

engineers as technical support, the e-tutors, the e-learners, and the Greek

authorities. The directors and the engineers were not Greek teachers. The e-tutors

had a twofold role, the moderator and the e-tutor. There were no Greek teachers’

online community managers at the time of the research and I was a member of the

Online Community Managers Association, called E-mint (http://emint.org/). E-mint is

widely known for members’ genuine interest and creative inputs in the field of online

communities. Among other results, thematic analysis revealed a template for writing

online messages, and a community management framework (Appendix I).

I also participated in the Moodle-based Leonardo DaVinci project ‘e-Tutor’

(http://pegasus.clab.edc.uoc.gr/ite/) and the Greek English language teachers’ forum

(www.pekade.gr/forum/). The aims were to identify:

• the Greek teachers’ ability of working online;

• soft skills in online environments;

• the ability to incorporate learning derived from discussion forums for

educational tasks and working conditions; and

• the potential for professional development via e-learning.

The results revealed that the Greek teachers had difficulties in integrating new

practices learned from online seminars in their teaching and learning practice. The

main reasons were the lack of training, lack of opportunities, lack of soft skills, and

absence of professional guidance, help and support.

Lastly, I acquired the opinions of the ‘Greek Primary Teachers’ Association for the

Valorization of ICT in Education’ (EEEP, http://www.eeep.gr; formed in December

2003). Fourteen out of 61 participants (22,95%) responded to a questionnaire in July

and August 2004. The factors that appeared to influence members’ participation,

were: (a) organisational, related to educational authorities; (b) school-based; (c)

personal: age, gender, training or absence of training on the use of computers, years

of teaching, previous experience and familiarization with ICT, writing and typing skills,

and personal characteristics; and (d) “the real world”: for example, expensive rates

for the internet access in Greece, the Internet connection from the schools,

participants’ spare time and time available for training. (The results of these studies

have been published in Lambropoulos 2005a, 2005b, 2005c.)

The overall findings suggested changes on a social cognitive/learning, and technical

level. The Greek teachers were not familiar with the new technologies: soft skills for

online collaboration were almost absent, and communication was fair. Professional

help and support was not available as regards e-learning, and lastly, Moodle

modules were not facilitating the communication gaps. One interesting observation

was the importance of timing regarding 4 spots in a community life-span:

1. Registration – enrolment and initial contact with the community,

2. One to two days after the registration,

3. One week after the registration – towards full participation, and

4. Maintenance of the community

These stages appear to be important; for example, initiations and interventions need

to be applied after the first week in order to allow time for the e-learners to familiarise

with the system and the community. The next section investigates the context of

educational authorities and GSN.

4.2 IDENTIFYING INTENTIONS

Intentions determine the stakeholders’ goals and acknowledge the real need

and leads towards adaptation of the right attitude to accept and incorporate change.

In the case of the Greek School Network (GSN), passive participation may be the

real need or a circumstance serving as visible evidence of a different need. GSN

initially attempted to provide an online environment for Greek teachers’ training and

professional development but the legislation and pedagogical frameworks were not

there to support teachers’ involvement. The Greek Ministry of Education and

Religious Affairs introduced GSN as the educational intranet to provide certified

telematic services for all schools and teachers in Greece. Moodle was used for the e-

learning service to host and distribute digitized e-lessons, for teachers with different

specialisations working in primary, secondary state schools, and adult centres

(Figure 4.2-1):

Figure 4.2-1. Organisation of the Education System in Greece 2003/04

(Euridice, 2003:6)

The Moodle@GSN teachers are located within the black arrow area; they teach

different subjects and have different roles in the Greek education system. GSN asked

e-tutors and teachers to participate on a voluntary basis.

E-Learning at GSN aimed to support Greek teachers’ life-long learning; however,

there were problems. For example, they could not acquire a valid certificate because

associated legislation was absent. More particularly, legislation (Law#3328,

01/04/2005) has prohibited online certification and accreditation provided by

educational organisations, unless this was part of their constitution so e-learning was

not considered as part of the national policy. Evidence refers to the first distance

education students registered at the British Open University in 1970

http://www.open.ac.uk/about/ou/p3.shtml. The first students registered at the Greek

Open University in 1998 (http://www.eap.gr/general/history.htm). Even today, there is

difficulty apply for a job in a governmental organisation if the degree is acquired via

distance learning (personal communication via email with Efthimios Kalaitzidis, MSc

graduate with special needs from Manchester University, UK; 08/12/2006). Unclear

criteria to provide rewards have been reported as a blocking factor for e-learning

quality (E-Quality project, 2006).

The Greek teachers talked about absence in governmental planning on pedagogy,

technology, and legislation. The right attitude, shared vision, and legislation to adopt

change were absent. This was an observation in discussions with the teachers in

schools, seminars, conferences, and emailing lists. Evidence to support this

observation came from a recent PhD on investigating Greek teachers’ needs and

training design; Tsetsilas (2006) reported:

• teachers’ training needs at school level were concerned to the social relations

and collaborative activities within the school environment;

• teachers needed support and training in collaboration, practical application of

innovations as part of scientific and professional training;

• there was lack of self-esteem and self-confidence derived from insufficient

training (Tsetsilas refers to “insufficient cognitive equipment”, 2006:6);

• the basic characteristics of the Greek educational system and the official

educational policy was centralism, restrictions in school autonomy, insufficient

basic and ineffective professional training; and

• certain parameters in the school environment required training.

Tsetsilas found that teachers currently exhibit insufficient professional skills on a

social and collaborative, cognitive/learning, and technical level. Lack of new

capabilities may result in inability to communicate their subjects with the students,

and lack of communication and collaboration within their environment. Tsetsilas

proposed that an in-service training program could be planned and organised

according to the training needs and suggestions of the Greek teachers themselves.

Alekos Alavanos, a Greek MP, representative of the Communist Party, reported this

problem to the Greek Parliament (24/11/2006 -

http://www.syriza.gr/modules/news/article.php?storyid=777; last access 05/06/2007).

In his speech after the Greek teachers’ 6 weeks strike, he said that everyone

involved in Greek education realises the need for change. It is interesting to see that

the Greek teachers’ demonstrations continued every Wednesday until this section

was written (18/02/2007). Therefore a risk analysis was needed (Appendix II).

Overall, it appears that there were discrepancies between the stakeholders’ goals,

common ground and right attitude are not established. However, there is space for

improvement on a social, cognitive, and technical level.

4.3 PLANNING

Ethnotechnology can capture relevant information for planning in e-learning

engineering. The first section described the Greek teachers’ context; this section will

refer to the e-learning environment.

4.3.1. MOODLE@GSN: Moodle at the Greek

School Network

The Greek School Network (GSN) is the educational intranet similar to the

British JANET (Vivitsou et al., 2008). With regards to the e-learning service,

evaluation of various open-source learning management systems led its developers

to the open source package Moodle (Modular Object Oriented Dynamic Learning

Environment; http://www.moodle.org). The GSN e-learning platform is called

Moodle@GSN (http://e-learning.sch.gr). The Greek teachers played the roles of both

the course creators and students on a voluntary basis. Moodle@GSN is an

autonomous, self-organised service for teachers’ distance education training (Figure

4.3.1-1):

Figure 4.3.1-1. Moodle@GSN research context

Moodle@GSN

4.3.1.1 Users and Activity in Moodle@GSN

Several observations and studies were conducted at Moodle@GSN as part of

time-series design. Two studies appeared to be significant for its history. The first

study was an overall quantitative evaluation until the 01/11/2006 (Vivitsou,

Lambropoulos, Konetas, Paraskevas & Grigoropoulos, 2008). Then, a baseline study

drew the line before and after any implementation in GSN based on descriptive and

discourse analysis.

Moodle@GSN started in 2003 with 2 online courses. Nine more courses were

created in 2004, 2005 and 26 in 2006, in a total number of 46 courses. The baseline

was the 1st of November 2006; on this date, there were 1,910 users registered online

whereas 64 users were registered in the 14 courses that were under construction. In

a total number of 4,350 members, there are 853 registered active participants, and

25 e-tutors. This means that 19% of the total number of registered users exhibited

some kind of activity (e.g. visiting the online courses, posting in chats and

discussions) in Moodle@GSN and 3% were the e-tutors. Due to the fact that

participation was on a voluntary basis, the offered courses had an open nature and

were divided in two major categories, the structured and well managed and the

courses that were designed for a special interest (e.g. Yoga, bird watching). With the

subject as the criterion, the categorization of the online course (Table 4.3.1.1-1):

Table 4.3.1.1-1. Courses categories and number of e-learners

General Topic # Courses #e-learners Familiarization with Moodle 3 16 General Interest 6 98 Greek Schools Network Training 3 59 Greek Language 1 57 Pedagogical Approaches 2 124 IT Training 10 1167 Multimedia 2 202 Open Office 4 124 Courses Under Construction 15 63

Total 46 1910

It appears that there were 1,910 e-learners in 46 Moodle@GSN courses. More

specifically the categorization was as follows (Figure 4.3.1.1-1):

Online Courses in GSN

1 2 3 4

Category

Familiarization w ith Moodle

General Interest

Greek Schools Netw orkTraining

Greek Language

Pedagogical Approaches

IT Training

Multimedia

Open Office

Graph 4.3.1.1-1. Online course categories in Moodle@GSN

It appears that in 46 completed and courses under construction there were 1,910

Greek teachers having a preference in IT training, multimedia, as well as the use of

pedagogical approaches. From the overall 206 messages sent in these courses, 8

discussion threads started from the e-tutors and 18 from the e-learners themselves,

resulting in 132 messages from the e-tutors and 74 from the e-learners There were

94 new topics of discussion launched by 34 e-tutors. In 22 courses there were chats,

having 1,000 messages sent by 138 participants. In addition, 40 quizzes were

activated in 19 courses used by 106 users in 197 efforts to solve them. Lastly, there

were 67 assignments in 18 courses from 47 users in a total of 94 submissions.

The 1st of November 2006 (baseline) was the starting point of interventions. There

were two interventions, collaborative e-learning and the use of tools based on the

proposed underlying conceptual frameworks. Part of the collaborative e-learning

intervention was the introduction of community management by the investigator. It

consisted of material providing advice on how to better use the platform including

emoticons. It also had material intended to improve the participants’ soft skills for

effective communication and about collaborative e-learning principles (Appendix VI).

The second intervention was to provide access to the new tools.The following table

describes the type and the number of messages. The ratio of single messages

26.6%, in a total number of 206 messages, 16.5% were the messages with a reply,

and 56.7% were the overall replies. In addition, it appears that there is counter

analogy to the number of messages and the number of replies, for example 19

messages had 1 one reply, whereas 1 message produces 27 replies (Graph 4.3.1.1-

Number of messages and replies

1 2 3 4 5 6 7 8 9 10

Number of Messages

Number of replies

Graph 4.3.1.1-2. Comparison between number of messages and replies

This message was initiated to test the e-mint community managers’ suggestions;

they had to talk about their experiences and the Greek teachers responded

enthusiastically. The intervention stopped in order not to interfere with the study.

From the total number of 32 courses, two courses produced the aforementioned

messages. One course was built before the intervention, and the second after.

The messages in the first course ‘Use of ICT in Religious Education (RE)’ on the

discussion topic about the use of Power Point presentation were limited as regards

the richness of the text. The messages were sent during the period 26/03/2006 -

29/03/2006. There were 28 words in 6 threads. Even though the discussion is limited

there is evidence of collaborative learning. The participants (all different individuals)

built on each others’ threads and agreed on the importance of collaboration as

follows:

1 Participant A: Η παρουσίαση είναι τρόπος παράδοσης αλλά και εξέτασης The presentation (ppt) is a way of delivery and examination.

2 Participant B: συμφωνω I agree

3 Participant C: Και κάνει το μάθημα πιο ενδιαφέρον (χρήση οπτικοακουστικού υλικού).

And makes the class more interesting (use of audiovisual material) 4 Participant D: Και δεν κουράζει τους μαθητές.

And is not tiring for the students 5 Participant E: Ενδιαφέρουσα κ΄συλλογική συνεργασία

Interesting & collaborative cooperation 6 Participant F: ΠΡΟΠΑΝΤΩΝ ΣΥΝΕΡΓΑΣΙΑ

MOST OF ALL COLLABORATION

Participant F stressed the importance of collaboration using capital letters. In the

second discussion of the same first course (22/03/2006 - 09/05/2006) there were 13

messages with no more than 2 sentences in each thread. It appears that the

participants were exploring the environment; they were reluctant to reply since they

did not know each other (Participant F: ‘Βάλε φωτογραφία για να δεις βοήθεια. Έτσι

δεν έχεις ελπίδες......’ Add a photo to find help. Otherwise you don’t have a chance…

(26/03/2006)’. This message triangulates the previous observations on interventions

as regards the provision of professional help and the need for collaboration.

Next, the participants were invited to the second course on project management, built

from the researcher with the help of two colleagues, Marianna Vivitsou and Dimitris

Konetas. The participants were given educational material (samples exist in

Appendix VI) and the e-tutors followed the online community management framework

(Appendix I). The course “Project Method” was designed to respond to the Greek

educators’ need for training on educational project management, institutionalised by

law (Greek Government Gazette 303 & 304/13-3-2003).

The number of visits and the number of messages sent were (Table 4.3.1.1-2):

Table 4.3.1.1-2. e-Learners’ posts and views in the 6 active courses

E-LEARNERS’ POSTS AND VIEWS Online Courses Forums Discussions Users Posts Views 1 Initial Page GSN News GSN community 4576 7 6532 ICT in R.E. The Use of Ppt. Ppt use 15 5 93 Project Method e-tutors discussion Intro 50 4 54 Project Method Initial problems What we want 50 6 185 ICT in R.E. ICT in RE ICT in RE 15 7 106 Project Method Projects4discussion Hi everyone 50 5 13

Total 4576 34 708

It appears that 4,576 users posted 34 messages with 708 views. The course under

construction for this study appeared to have initiated a significant number of posts. A

comparison demonstrates the rapid increase of the messages in the course “Project

Method” after the initiation of the community management scheme (Table 4.3.1.1-3):

Table 4.3.1.1-3. e-Learners’ replies and dates

E-LEARNERS’ POSTS AND DATES

Online Courses Forums Discussions Replies Dates

1 Initial Page GSN News GSN community 27 10/03/2004 - 23/02/2005

2 ICT in R.E. The Use of Ppt. Ppt use 5 26/03/2006 - 29/03/2006

3 Project Method e-tutors discussion Intro 7 11/06/2006 - 19/07/2006

4 Project Method Initial problems What we want 9 04/06/2006 - 06/10/2006

5 ICT in R.E. ICT in RE ICT in RE 12 22/03/2006 - 09/05/2006

6 Project Method Projects4discussion Hi everyone 14 17/10/2006 - 01/11/2006

Total 74 10/03/2004 - 01/11/2006

The e-learners, all different individuals, produced 14 threads with more than 2,000

words in total with the Project Method course among them with 30 replies between

04/06/2006 and 01/11/2006 presenting the following activity in the first week (Graph

4.3.1.1-3):

Activity in the Online Course

28, 22%

77, 62%

13, 10%

Number of Topics

Number of newdiscussionsNumber of sentmessagesNumber of activeparticipants

Graph 4.3.1.1-3. Activity in the online course

It appears that the there was initial significant activity after the baseline and the first

intervention; there were 8 topics, 28 new discussions, 77 sent messages and 13

active participants. From the total number of 45 participants, 71% were passive and

29% active participants with an average of 6 messages per poster. Overall, it

appears that Moodle@GSN has potential to initiate an active e-learning community. It

is evident that:

• Professional development anchored in e-learning is one of both GSN and the

Greek teachers’ targets.

• The Greek educational authorities, responsible for planning and support, were

absent on a pedagogical and legislation level.

• The main areas of training were suggested to be IT training, the use of

multimedia, and current pedagogical approaches.

• The Greek teachers lacked appropriate e-learning training.

• The Greek teachers themselves attached importance to the key variances of

collaboration and social interactions evident in their discussions in an explicit

and implicit way.

Considerations on a socio-cultural, pedagogical and technological level were directed

to supporting social interactions and collaboration in order to activate participation in

collaborative e-learning.

The interventions in this research were the support of collaborative e-learning and its

social aspects in particular as well as the introduction of a set of new tools to support

passive and active participation levels, interactions, and the collaborative e-learning

as such. Thus, the studies were as follows (Table 4.3.1.1-4):

Table 4.3.1.1-4. E-Learning Engineering for Moodle@GSN

E-Learning Engineering for Moodle@GSN Date Sample Environment Intervention Activity

Ethnotechnology

1 1/07/2004 -30/08/2004

EEEP mailing list Mailing list n/a

Researcher’s Participation in the list - Questionnaire

2 14/04/2004 -30/06/2004

E-mint online community managers

Mailing list n/a Researcher’s Participation in the list - Discussion

3 21/03/2006 -07/04/2006

Greek education mailing lists, EFQUEL list

Moodle@GSN & E-mmersion

-Learning Management -Tools

Online course: Introduction to Web Design

4 01/11/2006 -30/11/2006 Moodle@GSN Moodle@GSN Learning

Management

Online course: Educational Project Management with Collaboration Tools

5 06/03/2007 -13/03/2007

Greek Moodle developers lists

E-mmersion Tools Recommendations for new tools

6 01/03/2007 -31/03/2007

PSD e-mail database

REFERENCES Dourish, P., & Anderson, K. (2006). Collective Information Practice: Exploring Privacy

and Security as Social and Cultural Phenomena. Human-Computer Interaction, 21(3), 319-342.

Fernandes, C., & Montalvo, A. (2006). E-Quality Synthesis Report: Experience-based Quality in European ODL.

Golafshani, N. (2003). Understanding Reliability and Validity in Qualitative Research. The Qualitative Report, 8(4), 597-607.

Lambropoulos, N. (2005). EEEP Online Community of Practice: The First to Boldly Go in Greece. "Open Education", The Journal for Open and Distance Education and Educational Technology, 2, 29-56.

Lambropoulos, N. (2005). Paradise lost? Primary Empathy in Online Communities of Interest and Ways of Use. Paper presented at the 1st Conference on Online Communities and Social Computing, in the 11th International Conference on Human-Computer Interaction 2005, 22-27 July, Las Vegas, NV. Retrieved 05/09/2005, from http://www.intelligenesis.eu/nikiweb/PDF/05/lambropoulosOnlineEmpathyVegas05Research.pdf.

Shackel, B. (1991). Usability – Context, framework, definition, design and evaluation. In B. Shackel & S. J. Richardson (Eds.), Human Factors for Informatics Usability (pp. 21–37). New York, NY: Cambridge University Press.

Tsetsilas, I. (2006). Reporting teachers' training needs and design training schemes: The case study from a primary school using D.I.O.N. model. Καταγραφή επιµορφωτικών αναγκών των εκπαιδευτικών και σχεδιασµός προγραµµάτων επιµόρφωσης: Η µελέτη περίπτωσης µίας σχολικής µονάδας της Πρωτοβάθµιας Εκπαίδευσης µε το µοντέλο D.I.O.N. . Unpublished research at the Open University, Patras, Greece.

Vivitsou, M., Lambropoulos, N., Konetas, D., Paraskevas, M., & Grigoropoulos, E. (2008). The Project Method e-course: the use of tools towards the evolution of the Greek teachers’ online community. International Journal of Continuing Engineering Education and Lifelong Learning (IJCEELL), 18(1), 26-39.

Tools & Evaluation Techniques for Collaborative E-Learning Communities Ch. 5: Tools & Evaluation Techniques

Tools & Evaluation Techniques Supporting Collaborative E-Learning Communities

• Presentation of the first models for tools and evaluation techniques

• Initial evaluation of tools and evaluation techniques

• Applying guidelines and heuristics from feedback for design

• Implications for e-research design

• Iterative design and e-research design

Chapter 5 presents the initial design and evaluation related to the conceptual

frameworks, the tools prototypes, the evaluation techniques, and the research

design. Three studies are presented, one with international participation, one with the

Greek teachers, and one focus group with Greek teachers who are also Moodle

developers. Guidelines and heuristics obtained from feedback on the proposed

concepts and tools.

5.1 INTRODUCTION

Six tools1 were initially considered for integration in Moodle, and 3 tools were

found which were either not working for the Greek context or not suitable to be

discussed here; these tools were:

1. A chatbot, that initiated ‘safe’ conversation for passive participants

(Lambropoulos, 2007), was built in ASCII (American Standard Code for

Information Interchange); ASCII was found difficult to be represented in Greek

characters.

2. A keyword search facility that was not used. According to one of the

participants, it was a great idea but current systems are not built to support

such tools.

3. A real-time pedagogical usability questionnaire that was not particularly used.

The collaborative e-learning tools to be discussed here are:

1. Social network analysis tools

2. Participation levels evaluation graphs

3. Tools to structure collaborative e-learning

The following sections refer to the design process of these tools.

1 The tools were developed by Intelligenesis, a British company specialising in market research, social networking and e-learning.

5.2 COLLABORATIVE E-LEARNING

This section will present the iterative design process from creating the first

designs to the actual re-design and implementation. Four projects (blocks) were

developed, two of them will be discussed here (Table 5.2.-1):

Table 5.2.-1. Iterative Design Blocks

ITERATIVE DESIGN

Blocks Sample Environment Intervention Activity

1 21/03/2006 -07/04/2006

Greek education mailing lists, EFQUEL list

-Learning Management Tools

Online course: Introduction to Web Design

2 01/11/2006 -30/11/2006 Moodle@GSN Moodle@GSN Learning

Management

3 06/03/2007 -13/03/2007

Greek Moodle developers lists

E-mmersion -Tools Recommendations for new tools

4 01/03/2007 -31/03/2007

PSD e-mail database

Block 1 and 3 will be discussed in this chapter. Block 2 tested the community

management as part of collaborative learning framework, and will only be used for

comparison. Block 4 will be discussed in the next chapter as the main study.

5.2.1. Design for initial design: Create prototype testing by the e-learners

Simplicity in design helps learners to concentrate on their objectives (Boy,

2007; Alty, 1997). This means that one of the targets in e-learning design should be

simplicity in order to maintain e-learners’ cognitive stability. Targeting the sense of

community development and socio-cultural learning, the tools were designed to

support presence and co-presence awareness, participation evaluation, and

5.2.1.1. Presence & Co-Presence Awareness: Visualisations Interactions Tools

The literature revealed that observing and analysing social interactions can

increase collaborative learning understanding. JUNG Social Network Analysis (SNA)

open source software was found to be suitable to acquire real-time results. Social

interactions can be depicted in SNA Nodes and Centrality windows as Visualisation

Interactions tools (VIT) open as Java applets using algorithms (Figure 5.2.1.1-1):

(a) (b)

Figure 5.2.1.1-1. Visualisation Interaction Tools (VIT) Nodes and Centrality

Each node represents a unique user/learner and the number of messages is

indicated as numbers as well as on the interaction lines; the more the messages, the

thicker the interaction lines. The Java applet uses JUNG library to create a sparse

graph, where users are represented as vertices and their relations as edges. The

process is as follows (Figure 5.2.1.1-2):

Figure 5.2.1.1-2. Visualisation Interactions Tools (VIT) production line

Moodle was patched to create a link which passes the forum ID to a Java applet. The

applet executed PHP script that fetched all required information from the Moodle

database creating an XML file, with all calculations made such as user relations and

message count. Then XML passed to the JAVA applet and the JAVA applet built a

graph based on information generated from the XML file.

The hosting company upgraded PHP4 to PHP5 and constantly reconfigured PHP5 and

Apache; JPGraph, the graphing software creator, was not updated, whereas GD library

was not activated. GD creates PNG, JPEG and GIF images and is commonly used to

generate charts on the fly. Not being activated after the upgrade resulted in major

problems with the use of these tools; the images did not display correctly and were

represented by an X. Participant D1 expressed his frustration: ‘It keeps driving me

bananas all the time. It really gives me the willies when that peculiar X appears in the top

lefthand corner’.

Despite the problems, e-tutors and e-learners would be able to observe the

sociability of the human network.

5.2.1.2. Participation Awareness: Participation Evaluation Tools

Participation awareness is related to presence and co-presence awareness

measured by course participation and discussion participation graphs. Participation

Evaluation Tools (PET) are two graphs showing the participation levels for the overall

course activity and the e-learner’s activity in one discussion (Figure 5.2.1.2-1):

Figure 5.2.1.2-1. Course and individual participation levels graph

The graphs were built as follows (Figure 5.2.1.2-2):

Figure 5.2.1.2-2. Participation evaluation graphs production line

Moodle was patched in order to auto-generate links with the course ID that pointed to

PHP scripts in order to enquire users’ database accessing the specified course. Then

it gathered all statistical information from databases, parsed information and passed

it to JPGraph library in order to perform an output on the screen in real-time.

5.2.1.3. Structuring Collaborative E-Learning: MessageTag

The tool to structure collaborative e-learning followed Collaborative e-

Learning Episode (CeLE). The initial tagging was inform, explain, explore, evaluate,

and other, was structured onto a drop down menu that was designed and located

after the posting text box. This was because posters may not recognise the type of

the reply unless they finished their message. It also contradicts the existing models

and tools; drop down menus and message tagging or openers have been designed

as an initial requirement (Figure 5.2.1.3-1).

Figure 5.2.1.3-1. Initial Design for Message Tagging

The script for such a tool is very simple, written in PHP and HTML and can be

incorporated in any Post page. Moodle was patched to allow all messages stored in

the database to be tagged. In addition to the tool, SQL queries could be performed to

get different statistical information based on message types or complex statistics

where types are only a part of a query (for example keyword and message type that

was already implemented but not used). The use of icons was considered instead of

text as used in the “vicarious learner” project (Lee et al., 1999). However, it was

thought that there will be excessive iconic information on the interface and, since the

e-learners actually read the title and the actual message when they post, the use of

text would not interrupt their reading but can be part of it.

Overall, it is anticipated that the tools can broaden and illuminate the space between

human-human interactions so as to open space for reflection for the e-learners. From

a research viewpoint, the tools could expand our understanding on the socio-

cognitive aspects of collaborative e-learning.

5.2.2. The E-mmersion Block

The first block for iterative design to acquire participants’ opinions was

conducted from 21/03/2006 to 07/04/2006. The aims were:

The call for participation was sent initially to registered users in the web design

course at Moodle@GSN; only 5 out of 128 registered users responded to the call

(28/01/2006). Help was sought and found from the European Foundation for Quality

in eLearning (EFQUEL) (http://www.qualityfoundation.org/). The call was also sent to

the most popular Greek educational mailing lists, EEEP and PEKADE as well as

EFQUEL, and was announced on EFQUEL front page.

The online course in the experimental environment was supplementary to the web

design course in Moodle@GSN. From the 68 initial subscribers 12 did not enrol. The

remaining 56 participants are shown in the following graph (Graph 5.2.2-1):

Participating Countries

43, 64%

13, 19%

2, 2%1, 1%1, 2%1, 2%1, 2%1, 2%1, 2%1, 2%1, 2%

GreeceUKHungaryGermanyIndiaPortugalSpainSwedenSwitzerlandUSATurkey

Graph 5.2.2-1. Participating countries

The majority of the participants were from Greece (n=43, 64%) and the UK (n=13,

19%). The participants were divided in two groups and worked in two research pools,

the web design course for the Greeks and a discussion to evaluate the tools for all.

Also, there was a ‘Living Room’ for all participants. The participants were free to

communicate in both languages, English and Greek, however, English was proposed

in the tools evaluation discussion.

Methodology: A questionnaire was distributed and the collaborative e-learning

analytical framework was used for messages analysis. The suggested research

methodology proposed messages analysis, logging, and questionnaire statistical

analysis. The demographics, messages quantitative analysis and a collaborative e-

learning episode example from the web design pool are presented in Appendix VII.

Four CeLEs were identified in the Web Design pool with the Greek teachers. The

total code network view was depicted in ATLAS.ti (highlights added by the author):

Figure 5.2.2-1 Total Codes Network in the Web Design pool

Figure 5.2.2-2 shows the code network for the 4 CeLEs in the Web Design pool. The

codes were: initiation, explanation, agreement, conflict, exploration, evaluation, new

ideas for co-construction, and other. After the analysis, it appeared that social cues

can be a separate attribute for the CeLE framework. Additionally, disagreement was

collapsed with agreement as they are opposite without being separate.

The next section presents the results from the second pool relevant to this chapter,

the tools evaluation pool.

5.2.2.1. Tools Evaluation Pool

In the tools evaluation pool there were 7 low, 2 medium and 1 high activity

user and a total of 33 messages were sent. (The high activity user A1 was the

Swedish Moodle developer.) (Figure 5.2.2.1-1):

Figure 5.2.2.1-1. Participants and number of messages (ATLAS.ti)

In addition to the pattern for writing online messages from the E-mint study, a second

pattern was identified and used (Appendix A_I_2).

Visualisation Interactions Tools (VITs): There were two graphs providing

information about the locus of participants within one discussion in a forum, based on

Social Network Analysis and the levels of participation. The two tools were located on

the top of discussion (Figure 5.2.2.1-2) and were VIT Nodes (Figure 5.2.2.1-3) and

VIT Centrality (Figure 5.2.2.1-4):

Figure 5.2.2.1-2. Location of VIT on the discussion forum

Figure 5.2.2.1-3. VIT Nodes

Figure 5.2.2.1-4. VIT Centrality

In the discussion in English language, A1 was initially sceptical on using algorithms

and Java compared to PHP applications. He was not familiar with sociogrammes but

found them interesting and mostly useful by moderators: ‘It would be interesting to

see who is active and in what role and what contributions people make. I think it is

the teacher's job to e.g. monitor/moderate group work and see to it that the

assignments are distributed evenly and that credit is given fairly… [resulting in] better

learning.’. M1 as an online tutor she ‘would like to know which students are active

and participate in the e-lessons and which not. I would use it in me lessons!!’. M1

liked VIT as ‘vit nodes also work with me and i agree they can be very useful for

class participation statistics (quality measurement)’. However, she could not

understand the concept of centrality and had to read the instructions. Also, AM, GF,

M2, and D1 expressed the same problem. E1 expressed her unfamiliarity with the

tools as well: ‘I'm not familiar with what they stand for, so I'm afraid I can't be of much

help here. They seem nice, though!’.

A1 suggested that learners ‘can lurk intensively and actively and learn more than

those visibly active’, so she proposed passive participation to be visible on VIT. The

participants had to face new concepts and work with new tools without previous

experience. Participant M1 suggested: ‘…i (at least tried to) familiarised with new

concepts (quality, e-/web/online learning etc)’; ‘through this experience I realised

(once again) that there are some many things left for me to ‘learn’ in the LMS

management area and the evaluation of technology-based learning. Also: Some

concepts need to be defined (e.g. what are ‘best learning achievements?”), some

applications / tools to be improved (e.g. philippa’s repertoire of responses), some to

be further explored (e.g. VIT tools, activity graphs, message tags) and the moodle

environment itself needs more elaboration (e.g. listening activities?)’.

Participation Evaluation Graphs: Two types of graphs were created associated with

the online course and the individual e-learner describing the e-learning community

progress (Graphs 5.2.2.1-1 to 5.2.2.1-3):

Graph 5.2.2.1-1. 31/03/2006 – 5/28 Graph 5.2.2.1-2. 04/04/2006 – 10/28

e-learners e-learners

Graph 5.2.2.1-3. 08/04/2006 – 10/28 e-learners

As viewed in the previous graphs, only two members appeared in high and medium

activity during the first days (31/03/2006). Thus the moderator sent an email

suggesting that all participants need to contribute to the discussion. This intervention

appeared successful; 5 more participants appeared in the low participation graph

5.2.2.1-2 (04/04/2006).

M1 said that such a tool is not helpful: ‘for a newbie like me passive participation very

often proves to be very constructive’ (M1). E1 found difficulty in interpreting them. A1

said: ‘they show that e.g. my activity level in the Induction course is medium, that

there are 5 other users on low level and 1 user, probably admin with high level.’ To

A1 the kind and the quality of the activity is missing ‘or whether anything, and if so

what, may have been learnt.’, so log files provide more valuable information. E1 said:

‘they are more useful to teachers than fellow students.’. M1, talking about the sense

of community, said: ‘how can you, from in this way graphically presented statistics,

can conclude that someone is 'immersed'.’.

From an e-tutor’s and researcher’s viewpoint, the graphs were effective. Similar tools

exist in other learning management systems such as Blackboard, where bar graphs

depict e-learners’ overall activity rather than distinguishing passive and active

participation levels. There were some issues due to systems’ instability; the first

column of participation was unstable; passive participants were not shown on the

graphs (participation column should have shown 28 participants in Graphs 6.2.2.1-1-

3). In addition, it was not possible to retrieve their log files. Other problems were

related to more than one login names registered for each user exhibiting multiple

appearances, indicating the need for an initial account confirmation to ensure

accurate and reliable results.

Collaborative e-learning tool MessageTag: The participants were encouraged to

use a drop-down menu for tagging their messages2 (Figure 5.2.2.1-5):

Figure 5.2.2.1-5. MessageTag

The tool was used more in the Evaluation Pool than the Web Design pool as follows

(Table 5.2.2.1-1) (only the participants’ messages were counted):

2 At this point in the study, disagreement was coded under evaluation. Later it appeared as on option in conjunction with agreement

Table 5.2.2.1-1. Use of MessageTag

USE OF MESSAGETAG

Pools Overall replies

CeLE Attributes # Tagged

messages Percentage

Inform 9Question 2Explore 4

Living Room

Explain 2

17/35 48.5

Inform 4Question 8Explore 5

Web Design

Explain 3

20/73 27.3

Inform 12Question 6Explore 2Explain 4

Tools Evaluation 47

Evaluate 2

26/47 55.3

Inform 25 39.6 Question 16 25.3 Explore 11 17.4

Explain 7 11.1

Total 155

Evaluate 2

63/155

It appears that MessageTag was mostly used in the tools evaluation pool with 26 out

of 47 messages tagged (55.3%) and less in the Greek teachers’ only pool with 20 out

of 73 messages tagged (27.3%). In the introductory forum (Living Room) 17 out of 35

messages were tagged (48.5%). Because the tool was integrated in discussion, the

log files are the same with the forum and discussion logs. Based on the tagged

messages, the inform tag was used more than the other tags (39.6%) and the

evaluate tag less (3.1%); 16 (25.3) messages were tagged as questions, 11 (17.4) as

explorations, 7 (11.1%) as explanations, and 2 (3.1) as evaluations.

A1 found this tool interesting whereas E1 said that she never saw a tool like this

before so she did not know the purpose it served or how it can be used (‘for statistics

maybe?’). She wondered whether ‘users read messages according to their tagging

(from a long list of messages). A help file next to "message tag" would be useful.

Perhaps the text of each tag could be accompanied by an icon.’. AM and M1 agreed

with E1. M1 said that ‘each tag provides a thematic categorisation of the reply.

personally i read all the replies to the topic i'm interested in no matter what the tag is,

perhaps because what matters is the content and not the title. it might prove more

useful for younger learners' induction to the system though’. G1 agreed with M1. A1

added that the tool would have worked better if it could show the very structure of the

discussion as not many people are capable ‘of seeing such structures by themselves,

this meaning that they are likely to miss, or misunderstand the crucial points. All

learners are not good at 'deep' learning.’. He suggested that this tool could be

involved into becoming an instrument ‘for learners to enhance their literacy i.e.

becoming better e-readers/listeners and e-writers/speakers, then that would certainly

be a 'huge step for humanity'’. A1 recommended some additional tags for

consideration:

• add/develop

• ask for additional information

• ask for clarifications

• confirm

• approve

• agree

• disagree

• offer conclusions

• point to resources

Overall, it appears that some issues influenced MessageTag functionality: the

instructions were not helpful; it was the first time the participants used such tools;

there were severe technical problems; and the participants thought that the tools

were more helpful to e-tutors. This may result in the increase of low and medium

active participation levels as in the previous example. Nonetheless, implications for

design, discussed in the next section, can improve tools’ usability and usefulness.

Lastly, it was evident that the use of MessageTag attributes was descending as the

level of reflection and higher order thinking was ascending. This finding stresses the

importance attached to the difference between information provision and knowledge

acquisition and that the tool can make this difference visible. In this way the e-

learners participants can moderate their own messages and use the tool to facilitate

their critical thinking skills development; as such, the e-tutors can support this

process. This will have an impact on the e-learning quality.

5.2.2.2. Application of guidelines and heuristics from feedback in design

Based on participants’ recommendations and the researcher’s experience

four changes were made on Visualisation Interaction Tools (VITs), participation

graphs, and MessageTag.

Visualisation Interactions Tools (VIT): Following A1’s recommendation the lurkers

were added in the VIT centrality that provided more space on the interface. A

disadvantage is that the Java applet restricts login names’ clickability (Figure 5.2.2.2-

Figure 5.2.2.2-1. Lurkers overall view in VIT Centrality (right)

Participation Evaluation Tools: The two graphs for overall course participation

levels and discussion participation levels had to depict all participation levels for all

participants so there were three changes (Figure 5.2.2.2-2):

• overall participation column was corrected;

• because e-tutors’ messages change the results, these messages were not

counted in the graphs. They can be counted if the e-tutor wanted to appear as

one of the participants so the messages were calculated again; and

• date and time were added.

Figure 5.2.2.2-2. Redesign of participation graphs

Participation Avatars: Based on A1’s proposition, a new tool thought to depict

participation levels and an overall view. After discussing this proposition with the

graphic designer MR and supervisors, the avatar appeared to be a good solution.

Based on the notion that the avatar is an Indian concept, and thus indicates different

energy levels in the human body (Isaackson, 2003), the avatar was designed as

follows:

• Zero participation (grey)

• Low participation (red, grey)

• Medium participation (red, blue, grey)

• High participation (red, blue, yellow)

The avatars were integrated on the threaded discussion view. This means that the

participants can compare collaborative e-learning structures and participation levels

in one glance. Lastly, the log files will be the same as the discussion forum log files.

MessageTag: First, two more values were added on MessageTag, Agree and

Summarise. A1 suggested adding conflict but the decision was made; conflict was a

subcategory used for coding only along with disagreement. So the new collaborative

e-learning episode analytical framework was redesigned (Figure 5.2.2.2-3):

Figure 5.2.2.2-3 CeLE MessageTag tool

Following A1’s recommendation for overviews, a messages overall view in the

threaded form was adopted. In this way the e-learners would be able to see the

internal structure of the message.

5.2.2.3. Implications for Research Design The findings indicated implications for design and research design:

1. Questionnaire: The e-learners did not use the real-time online questionnaire

(N=9/31, 29%); several changes were made so the questionnaire could be

sent via email:

• Three sections were elaborated and added:

o the initial sense of community identification was based on empathy;

then, a Sense of E-Learning Community Index was adapted;

o the learning section was expanded; and

o Pedagogical Usability targeted usability and utility in detail.

• An absence of collaboration with the Greek educational authorities on the

implementation of the tools, led to the addition of an extra question

targeted to Greek teachers’ communication and collaboration with the

Greek authorities.

2. Changes on coding: Following changes on MessageTag, the two new codes

“agree” and “summarise” were added in the collaborative e-learning analytical

framework.

3. Changes on the Collaborative E-Learning Episode (CeLE): Two structures

appeared to occur in a CeLE, a horizontal and vertical (see figure ..). The

horizontal structure referred to interaction between the participants and thus,

a horizontal and interactive direction of learning. The vertical structure exists

within the message of the participants and is related to her reflective and

evaluation processes, and thus, a vertical and individualised direction of

learning.

A Sense of e-Learning Community Index (SeLCI) was further investigated (Rovai,

2002; Preece & Maloney-Krichmar, 2003; Wright, 2004; Daniel, 2007). Rovai (2002)

worked on the role of spirit, trust, interaction, and commonality of expectations and

goals towards the development of the sense of community in e-learning. He also

suggested that there are additional elements in e-learning such as social presence,

social equality, small group activities, group facilitation, the teaching and learning

style as well as the community size. Preece & Maloney-Krichmar provided a

framework to support sociability and usability. For online communication they

stressed the need for common ground, sense of social presence, and empathy and

trust. To support the group dynamics online they suggested the use of social

networks and reciprocity, roles, rituals, norms and policies. Wright (2004) emphasised

the dynamics between elements in a Sense of Community Index and suggested that

there should be different indexes if the study has an educational purpose. Daniel

(2007), working on social capital suggested the importance of shared experiences,

interaction, common ground, trust, awareness, social protocols, and the use of social

networks. Anchored in the aforementioned recommendations as well as the findings

the Sense of e-Learning Community Index (SeLCI) was developed for community

evolution, sense of belonging, empathy, trust, intensity, collaborative e-learning

quality, social network analysis for global cohesion and centrality.

Thus, the research design was adapted as follows (adaptations in grey) (Table

5.2.2.3-1):

Table 5.2.2.3-1. Research Design

ETHNOTECHNOLOGY DESCRIPTION

1 Scenic Fieldwork

1. Participation in projects, conferences, seminars, online discussions of Greek teachers’ associations and schools in Greece

2. Documentation, manuals and presentations by the Greek educational authorities

3. Personal opinions, conversations, and emails 4. Richness of text

2 Pre-Questionnaire 1. Demographics 2. Conditions of working and learning over the Internet 3. Initial knowledge on collaboration

3 Logging

1. Frequency of visits 2. Number of active and passive participants 3. Active participation levels 4. Passive participation levels 5. Sense of e-Learning Community Index

• Persistence: depth of discussion threads • Density: formula 2aN(N-1) • Reciprocity: number of messages sent and

received • Intensity: levels of participation

4 Thematic Analysis 1. Collaborative e-learning episodes analysis 2. Sense of e-Learning Community Index

• Number of Collaborative e-learning episodes

5 Social Network Analysis

The Sense of e-Learning Community Index 1. Global Cohesion

• Density • Reciprocity • Cliques • Structural equivalence

2. Global Centrality • Centrality • Closeness • Betweenness

3. Local real-time nodes & centrality

6 Post-Questionnaire

1. The Sense of e-Learning Community Index • Community evolution • Sense of belonging to the e-learning community • Empathy • Trust: knowledge exchange, help and support • Collaborative e-learning quality: participants’

opinions 2. Usage and usability of collaborative tools 3. Professional development

7 Statistical Analysis

1. Examination of the data, missing data, normality. 2. Descriptive Statistics: crosstabulation, frequencies,

arithmetic means, standard deviations, and exploration

3. Correlation: Pearson correlation coefficient (r). 4. Inferential statistics: statistical significance, p-value

(Cronbach's alpha, α), and null hypothesis.

8 Intervention Analysis 1. Form of the effect: the level, slop, variance and

cyclicity 2. Its permanence (continuous or discontinuous) 3. Its immediacy (immediate or delayed)

Overall, PHP applications cannot easily work with algorithms and Java. This perhaps

indicates the need for new programming techniques to support systems

interoperability. Since such programming has not been used yet in available e-

learning management systems a new hosting company was needed to meet most of

the requirements. Furthermore, if such tools and evaluation techniques do not exist, it

is difficult for the participants to observe they are missing.

With the provided time and resources in this study only redesign of the tools was

feasible. The redesign was tested and developed further with the help of a focus

group of Greek teachers Moodle developers.

5.2.3 Greek teachers Moodle developers

Three individuals, being both Greek teachers and Moodle developers,

participated in a focus group targeting tools redesign before the Greek teachers’

renewed participation. The discussion was from 06/03/2007 to 13/03/2007. Three of

them returned the questionnaire so the demographics are as follows (Table 5.2.3-1):

Table 5.2.3-1. Demographics for the three Greek Teachers / Moodle Developers

Demographics

Age Gender Occupation Working

Experience (years)

Use of computer / software

(years)

Use of Internet

Use of Moodle

1 30-40 Male Teacher 1-5 6-10 All day 1-5 years 2 40-65 Male Instructor 11-20 6-10 All day 1-5 years

3 40-65 Male Doctor / instructor 11-20 1-5

Once -twice a day

1-5 years

All three were male, two between 40-65 years old and one between 30-40 years old

and none of them had participated in any of the previous blocks or studies. P1 was a

teacher, P2 an instructor, and P3 a doctor, all working, training adults using Moodle

for 1-5 years. P1 had 1-5 years of professional experience, he was using educational

software for 6-10 years, and he had been connected on the internet all day. P2 and

P3 had the same working experience, 11-20 years; P2 was using the Internet all day

and P3 once or twice a day. None of them said he knew any tools and evaluation

techniques to support participation whereas all of them thought participation

necessary. As for the reasons, P1 said that ‘self-efficiency is important in e-learning’,

P2 because ‘feeling part of the community’ is important, whereas P3 replied with a

question mark (‘?’).

The discussion took place in the experimental environment with 11 discussion topics

initiated by the researcher with a brief description of each tool. Thematic analysis

was used on the 53 replies to categorise participants’ opinions on the tools; in

addition, the new collaborative e-learning scheme was tested for use and usefulness.

The discussions topics were: an introduction, new ideas, tools, and suggestions on

Greek names. Only discussions on the new ideas and tools are presented here. The

comments about the tools on the provided questionnaire were (Table 5.3.1-2):

Table 5.2.3-2. Questionnaire open questions

Open Questions Results Participation Tools Message Tag VIT Nodes VIT Centrality Other

Show the quantity but not the quality of the messages. The avatar was simpler and equally good.

Structures information

Not needed, but not sure

Useful and interesting

P2 More information More tools

P3 Clickable images

Overall, the respondents said the following:

• E-learner’s participation graph was not calculated correctly.

• Understanding the usefulness of the MessageTag and VIT was not easy

without reading the manual;

o Simpler names were needed (P3).

o On VIT Centrality, the list with the lurkers’ login names was distractive

and perhaps it should be removed. As for the centrality circles, they

were quite understandable; it may be a good idea to use this image as

the VIT Centrality icon (P3).

• Graphics:

o Multicoloured avatars are not clear as regards their meaning (P3: ‘Η

πολυχρωμία ...είναι λίγο δυσνόητη’). The use of one colour for each

participation level may work better ( ) (P3).

o The more information existed on an icon, the less the participation,

especially for the people who are not familiar with such environments

(P3). In other words, an image should explain its own use (P2).

o The results should be available on the interface without the

user/learner having to click on them (P3).

• They would like more tools.

P1, P2 and P3 also answered the second session of the questionnaire based on a

Likert scale 1-5 and focused on efficiency and effectiveness, satisfaction (ISO DIS

9241-11, 1994), enjoyability, learnability, and overall evaluation for imagination and

satisfaction (Zaharias, 2004; Silius et al., 2003) (Table 5.2.3-3):

Table 5.2.3-3. Tools Pedagogical Usability Scores

PEDAGOGICAL USABILITY

1 Efficiency & Effectiveness μ = 3.9

Participation Tools Message Tag VIT Nodes VIT Centrality

μ 4.3 3.3 3.6 4.3 2 Satisfaction = 4

μ 4.3 3.6 3.6 4.6 3 Enjoyment = 4.5

μ 4.6 4.3 4 5 4 Learnability = 4

μ 4.3 4.3 4 3.6 5 Imaginative μ = 4.6 6 Satisfaction μ = 4.3

Overall Score μ = 4.2

The tools scored 4.2 out of 5 as regards pedagogical usability. This means that the

participants were overall satisfied with the tools but made additional

recommendations as seen previously. Lastly, there were some final propositions. P2

suggested that the interface should provide two views; an overall users/learners’ view

so the moderator can support the learners’ individuality; and a user/learner’s view for

self-organisation and self-learning. He also suggested the group format for e-learners

flexibility. In this way, a user/learner who lost his interest and lurked can be activated

in a different team. Finally, P3 indicated the problem spotted in the literature,

structuring or not structuring information: ‘I think I understood!!!no need for explaining

the use of tags. But is it necessary to make use of tags? Isn't it easy to understand

the nature of the writer's message?’

However, this measured was found inadequate to accurately measure utility and

usability for new tools. The Collaborative e-Learning Episodes (CeLE) was successful

and 7 CeLEs were identified.

5.2.3.1 Application of guidelines and heuristics from feedback in design

When this discussion finished the Greek teachers were in the middle of the

online course in Moodle@GSN (main study). Meanwhile work was carried out

collaboratively with another programmer to update the tools and she actively

participated in the course as an e-tutor. The considerations on design and research

design were:

• The participants did not immediately understand the usefulness of the tools.

This may partly be because they were not familiar with such tools, and partly

because of design.

• The names of the tools came from social network analysis references; the

participants did not provide any alternative names.

• The lurkers’ login names on VIT Centrality were not removed because there

was no other way to make them visible on the tool.

• Providing all information on the interface was found to be of poor usability

because of the information overload on the interface so no additional

information was provided.

• The use of one colour for each participation level did not show the

user/learner’s potential. However, this was a good idea and the high

participation graph was changed to yellow ( ). The proposed red colour was

found inappropriate due to alert signalling of red and usability purposes.

• The icons for the VIT were changed to icons acquired from a discussion.

• Two views of the tools, as well as having the tools in a group format could not

be implemented in a study such as this one. It is a bigger project and requires

team working as well as time and funding.

• The pedagogical usability questionnaire was elaborated in more detail.

• A combination of participation levels and CeLE from a bird’s eye view can

provide comparable information (Figure 5.2.3.1-1):

Figure 5.2.3.1-1. Discussion on tools’ Greek names

Following the graph, it appears feasible to compare collaborative e-learning values

and levels of participation. Due to limited space, this will be analysed further in the

next chapter.

Lastly, since the utility and usability attributes were found inadequate, they were

transformed; new attributes were anchored in Zaharias usability questionnaire,

focused on 5 out of his 13 suggested attributes (Zaharias, 2006:198-199) as well as

Preece and Maloney-Krichmar’s framework on sociability and usability for online

learning communities (2003). Further correlation analysis suggested the

interactivity/engagement and motivation to learn to be combined under ‘motivation to

participate’. Moreover,

• relative items were grouped under one attribute;

• the aim was to support a utility & usability overview of the tools related to

participation in collaborative e-learning communities;

• the questionnaire was tested twice with 2 groups of different participants with

3 members in each group to ensure that the items were adapted and included

appropriately in the questionnaire.

Considering users’ unfamiliarity with new tools the utility & usability questionnaire

items were developed as follows (Figure 5.2.3.1-1):

Figure 5.2.3.1-2. Pedagogical Usability Attributes

Overall, all participants agreed that the tools, and in particular the Visualisation

Interactions Tools (VIT) were useful and important, especially for the moderator,

because she can: direct and control online discussions; discover interlocutors’

weaknesses and strengths; activate the lurkers with specific questions; aid in team

building by “bounding” the team; and record the discussion. They also said that self-

efficiency is important in e-learning and feeling part of the community is what

participation is about, addressing learning on an individual and a social level.

From a researcher’s viewpoint, the numeric assessment provided by the tools and

evaluation techniques was successful. Despite the discrepancies with the graphics

and difficulty in understanding the meaning of the tools, the Greek teachers Moodle

developers were satisfied with the tools, they enjoyed using them, and asked for

The last part of this research is the main study discussed in the next chapter.

REFERENCES Alty, J. L. (1997). Multimedia. In A. B. Tucker (Ed.), The Computer Science and

Engineering Handbook (pp. 1551-1570). Boca Raton, FL: CRC Press. Boy, G. A. (2007). Perceived Complexity and Cognitive Stability in Human-Centered

Design. Paper presented at the HCII'07 - HCI International 2007 Conference, 22 – 27 July 2007, Beijing, China.

Daniel, B. K. M. (2007). A Bayesian Belief Network Computational Model of Social Capital in Virtual Communities. Unpublished Research, PhD Thesis, University of Saskatchewan, Canada. Retrieved 01/08/2007, from http://library2.usask.ca/theses/available/etd-07132007-141903/unrestricted/ben_m.pdf.

Isaacson, C. (2003). The Way of Yoga. London: Element Books. International Standards Organization. 1994. Ergonomicrequirements for offi ce work

with visual display terminals.Part 11: Guidance on usability (ISO DIS 9241-11). London: International Standards Organization

Lambropoulos, N. (in press). Preparing the On-line Learners: Information Provision and Intention Setting by Chatbots. In P. Shank (Ed.), Online Learning Idea Book. Hershey, PA: Idea Publishing.

Lee, J., McKendree, J., Stenning, K., Cox, R., Dineen, F., & Mayes, T. (1999). Vicarious Learning from Educational Dialogue. Paper presented at the CSCL'99 - Computer Supported Co-operative Learning, 11 - 12 December, 1999, Stanford University. Retrieved 12/12/2005, from http://portal.acm.org/ft_gateway.cfm?id=1150283&type=pdf&coll=portal&dl=ACM&CFID=15151515&CFTOKEN=6184618.

Preece, J., & Maloney-Krichmar, D. (2003). Online Communities. In J. Jacko & A. Sears (Eds.), Handbook of Human-Computer Interaction (pp. 596-620). Mahwah: NJ: Lawrence Erlbaum Associates Inc. Publishers.

Silius, K., Tervakari, A.M., & Pohjolainen, S. (2003). A Multidisciplinary Tool for the Evaluation of Usability, Pedagogical Usability, Accessibility and Informational Quality of Web-based Courses. Paper presented at PEG’03, 11th International PEG Conference: Powerful ICT for Teaching and Learning. 28 June - 1 July 2003 , St. Petersburg, Russia. CD-Rom.

Wegerif, R. (in press). Dialogic, Educational and Technology: Expanding the Space of Learning. New York: Springer-Verlag.

Wright, S. P. (2004). Exploring Psychological Sense of Community in Living-Learning Programs. Unpublished research, PhD Thesis, University of Maryland.

Zaharias, P. (2004). A Usability Evaluation Method for E-Learning Courses. Unpublished Doctoral Dissertation at Athens University of Economics and Business

Tools and Evaluation Techniques for Collaborative E-Learning Communities Chapter 6: Main Study

Main Study: The quasi experimental study on Moodle@GSN and the

research pool

• How initial difficulties were resolved in the main study

• Demographics and initial knowledge or lack of it

• Tracing active and passive participation

• The collaborative e-learning episodes in the service of e-learning quality

• Unfolding the Greek teachers’ sense of community

• How pedagogical usability and usability informed human-computer interactions

• How and why the intervention was successful

• Comparison with other contemporary studies

Chapter 6 presents the preparations, interventions, findings, and discussion of the

main study. There is an initial examination of the Greek teachers’ human-human

interactions for working and learning online. Then the levels of participation reveal

their passive and active presence in the course in comparison to the experimental

environment. The comparison continues with the quest for quality in their discussion

under the lens of the analytical framework of collaborative e-learning episodes. The

study also investigates whether a collaborative e-learning community exists using the

sense of e-learning community index. In addition, pedagogical usability and utility

values provide information about the Greek teachers’ human-computer interactions.

Finally, the intervention analysis and comparison with current research are presented

in this chapter.

6.1 INTRODUCTION

The aim of this study is to address the Greek teachers’ passive participation

in the e-learning environment provided by the Greek School Network

(Moodle@GSN). Because the Moodle@GSN technicians were reluctant to

implement the new tools, these tools were incorporated in an experimental Moodle,

version 1.4.5 as with Moodle@GSN. The online course was on the ‘Use of New

Technologies for Educational Project Management’, started on 01/03/2007 and

finished on 31/03/2007. I participated as the 5th e-tutor (Figure 6.1.1-1):

Figure 6.1-1. The e-tutors in the online course

A link in Moodle@GSN in the last week led the participants to the research pool.

Thus comparison was feasible between the two contexts, Moodle@GSN and the

experimental environment. The e-research methodologies used to aid e-learning

engineering were centred on ethnotechnology: fieldwork, logging, thematic and social

network analysis, and questionnaires. More specifically, the next section in this

chapter describes demographics, conditions of working and learning over the

Internet, and examples of Collaborative e-Learning Episodes. Then, it explores the

attributes of the Sense of e-Learning Community Index: community evolution, sense

of belonging, empathy, intensity, trust, e-learning quality; in addition, global and local

social network analysis will aid in investigating group cohesion and the importance of

social networking and collaborative e-learning. The evaluation of the new

collaborative tools is conducted by utility and usability evaluation. Lastly, intervention

analysis examines the overall success and compares the findings with other

contemporary research.

6.1.1. Initial activities

The initial email call for participation in the online course attracted insufficient

response and another call was issued. To improve communication flexibility, the

participants were given gmail accounts. The course had to be expanded by one more

week than initially planned; this resulted in having the experimental session the week

before Easter 2007. It had 4 sections, project management, blog, wiki, and

videoconference. The participants had to study the educational resources, create

their own context using the tool and evaluate its use. The evaluation of the

videoconference was conducted in the research pool after modifications to the

interface based on previous research carried out before hand into the effectiveness

of the system. Because interface and pedagogical modifications (Delich, 2006) as

well as methods and tasks (Draper, 1993) are interlinked, a decision was made to

change from an instructional (e-tutoring) to a student-centred )collaborative e-

learning) approach.

Two questionnaires were sent: one at the beginning of the course to gather

information about demographics and some background and one at the end with

questions related to the exploratory research questions. One hundred and seventeen

(117) participants returned the first and 59 the third questionnaire. Only 40

questionnaires from the participants who returned the first and third questionnaire

and appeared on both Moodle@GSN and the research pool were accepted for

analysis (Table 6.1.1-1):

Table 6.1.1-1. The questionnaires selection process

Accepted / Rejected Questionnaires

Number of Questionnaires Value Justification

Total 59 Returning Q1, Q2, Q3; participation in Moodle@GSN and the research pool

Accepted 34 Participation in all previous activities

Rejected 19 Not participating in either Q1, Q3 or Moodle@GSN and the research pool

Accepted for analysis 40 (67.7%)

Forty questionnaires were selected for analysis using the above criteria and were

given a unique number. Considering the total absence of activity and the ratio

referred to in the literature (20% lurkers’ response), the response ratio compared to

the initial expression of interest (117) was satisfactory (34.1%).

Even though 2.03% of the overall responses in the questionnaires items were

missing, this was a low percentage and did not impose any serious problems with the

subsequent analysis (Tabachnick & Fidell, 1996). When participants had failed to

supply a response this was treated as a no response rather than using the mean.

Correlation analysis was used to suggest the highly correlated factors in order to

integrate them in one variable. These results, the small initial sample in the trials and

previous absence of variables justification in the literature suggested that the

questionnaire items could remain the same. Hierarchical Clustering Explorer 3.0∗

(HCE) (Seo, 2005) was used for the examination of the data (Figure 6.1.1-2):

Figure 6.1.1-2. Normality overview for tools pedagogical usability and utility in HCE

The responses from the questionnaires were also screened for normality skewness

and kurtosis in HCE (e.g. Hair et al., 1998) to determine whether the variables are

“normal” enough to be analysed; skewness and kurtosis suggested that original

variables can to be used. (Tests of significance for skewness and kurtosis test the

obtained value against a null hypothesis of zero for a normal distribution.)

∗ HCE is a visualization tool for interactive exploration of multidimensional datasets to help users explore and understand multidimensional datasets by maximizing the human perceptual skills (http://www.cs.umd.edu/hcil/hce/).

6.2 DESCRIPTION OF THE RESEARCH

CONTEXT

From the initially registered 177 teachers, 49 never fully enrolled. The participants

were asked to create their profiles immediately after their registration. It was hoped

that this would create a co-presence feeling by getting to know each other before

their attempts for active participation. Of the remaining 128 participants, 36 created

illegible profiles due to Greek language encoding, and 95 participants produced

usable profiles. Most of the participants with Moodle profiles were primary school

teachers (n=36, 36%), and IT secondary school teachers (n=22, 28%). Based on the

initial questionnaires (N=40) there were 9 female (n=9, 22.5%) and 31 male (n=31,

77.5%) Greek teachers. The age range in the closed questions was created

anchored in the way teachers are hired and previous studies (e.g. Hlapanis &

Dimitrakopoulou, 2004), and was successfully tested in the preliminary studies.

6.2.1. Who are the Greek Teachers?

The analysis showed 1 participant between 20-30 years old (n=1, 3%), 14

between 30-40 years old (n=14, 36%), and 24 more than 40 years old (n=24, 61%) (1

missing). They participated from different parts of Greece, 16 from Athens (Figure

6.2.1-1):

Figure 6.2.1-1. Participants’ locations in Greece

This selection process assigned a representative sample of the teachers with a

special interest in the use of ICT in education in Greece (Figure 7.2.1-1; originally

retrieved 03/09/2007, from http://www.lib.utexas.edu/maps/europe/greece_div96.jpg):

6.2.2. Conditions of Working and Learning Online

The participants’ years in education, as well as their experience in computers

and Learning Management Systems (LMS) were (see data in Appendix VIII):

ICT in Education: Most of the participants have worked in the Greek education

system for more than 6 years (N=40). There were 2 new teachers (n=2, 5%), 10

teachers working for 6-10 years (n=10, 25%), 18 working for 11-20 years (n=18,

45%) and 9 more than 20 years (n=9, 22.5%). The participants have used computers

in education: 3 for 1-5 years (N=3, 7.5%), 14 for 6-10 years (n=14, 35%), 15 for 11-

20 years (n=15, 37.5%), and 7 for more than 20 years (n=7, 17.5%). However, their

familiarity with Learning Management Systems (LMS) is relatively low; the majority

have not used LMS at all (N=22, 55%) and 3 for 1 to 6 months (n=3, 7.5%). Only 13

participant have been using LMS more than one year (n=13, 32.5%) whereas one

participants said that she was using LMS for more than 6 years (i.e. less than 6 years

ago). This response may not be reliable since Moodle was only made available to the

public in November 2001 (Moodle e-learning history, retrieved 17/07/2007, from

http://docs.moodle.org/en/Online_Learning_History). The correlations between these

factors are (Chart 6.2.2-1):

Correlations between Time in Education, Use of Computers and LMS

0 years Months 1-5 years 6-10years

11-20years

20+ years

Time Scale

Years in employmentYears using computersYears using LMS

Graph 6.2.2-1. Correlations between time in education,

use of computers, and Learning Management Systems (LMS)

The previous graph presents that the use of LMS starts in early employment. This

result may be related to the short time LMS in education has been available; for

example Moodle@GSN was available to the public in August 2002. The use of

computers is in parallel with the years of employment. As for training on Information

and Communication Technologies (ICT) in education, most of the participants did not

attend courses in higher education but outside the formal Greek education system

(n=29, 72.5%). The vast majority did not have any training in LMS (n=26, 65%); 8

learned to use Moodle in an ICT course (n=8, 20%), and 3 within the official Greek

education system in graduate or postgraduate courses (n=3, 7.5%); one of the

respondents had 6-10 years and 2 had 11-20 years in education. As they were not

recent graduates, this means that their course was part of a life-long learning course

whereas LMS were not part of the curriculum. Lack of training and launching online

courses as initiatives on an individual basis has been reported as an e-learning

quality blocking factor (Fernandes & Montalvo, 2006).

Familiarisation with the social aspects of the Internet: The majority of the

participants used the Internet on a daily basis: 13 are on-line all day (n=13, 32.5%),

23 once or twice a day (n=23, 57.5%) and 2 every 2 or 3 days (n=2, 5%). Before the

study, the respondents seemed to think that the use and importance of profiles and

discussion forums are significant in e-learning; a small ratio responded on the Likert

scale as low and very low although the ratio of not answering these questions was

relatively high (n=8-13, 22–32.5%). Most of the respondents considered the use and

importance of profiles and forums is of average importance (n=4-9, 10-22.5%),

relatively high or very high: 14 participants have used profiles before (n=14, 35%)

whereas 18 think they are important in e-learning (n=18, 45%); 21 participants have

used forums (n=21, 52.5%) and the vast majority believe in their importance in e-

learning (n=26, 65%). Despite the fact that the participants use the Internet, and

because the Internet is mostly based on textual communication, it appears that they

might not know ways to represent themselves and talk in online discussions.

Overall, the Greek teachers use the Internet regularly and participate in discussion

forums. On the significance of co-presence and e-learning management, they think

that profiles and discussions forums are of average importance. Their opinion was

checked in the final questionnaire and appeared to explicitly correlate communication

and the creation of profiles. Lastly, formal pedagogical training on ICT and LMS is

lacking. These results were similar to my observations and Tsetsilas’ findings (2006)

on Greek teachers’ lack of soft skills, lack of opportunities and professional training

incorporating current pedagogical approaches. In addition, Hartley (2007) suggested

the need for improving British teachers’ social and learning skills, self-instruction, and

their presentation on the web from a life long learning perspective. These results are

also reflected to the next findings.

6.2.3. Previous Knowledge of Collaborative

E-Learning Techniques & Participation

The Greek teachers replied to the question on collaborative e-learning

techniques and participation as follows (Table 6.2.3-1):

Table 6.2.3-1. Greek teachers’ knowledge and attitudes

on collaboration and participation

Collaboration & Participation

Yes No N/A Freq. % Freq. % Freq. %

Do you know... 1 collaborative ways for e-learning? 11 27.5 20 50.0 9 22.5 Do you think that… 2 your participation is useful? 26 65.0 0 0.0 14 35.0 3 active participation is necessary? 31 77.5 0 0.0 9 22.5

The previous table presents that only 11 participants knew some e-learning

collaborative techniques (n=11, 27.5%); however, most of them either said they did

not know or did not answer (n=29, 72.5%). As for their participation, most of them

said that their participation is useful (n=26, 65%); a significant number (n=14, 35%)

did not answer the question. The majority replied that participation in e-learning is

necessary (n=31, 77.5%), none denied that participation is not necessary, and 9

participants did not answer the question (n=9, 22.5%). The N/A response on

collaboration and participation as well as on the use and importance of profiles and

forums is relatively high compared to the response on questions about personal

details (n=1-3, 2.5-7.5%).

Overall, despite the fact that the Greek teachers did not know any particular

collaborative e-learning techniques, they believed that their own and other e-learners’

active participation is of great importance. This implies a gap between knowing the

importance of participation but not being able to act upon it because of lack of know

how. This result is similar to other results (e.g. Beaudoin, 2002; Gulati, 2006) and this

lack of knowledge of how to work and learn together is inherent in the teaching and

learning modes for teachers’ training found in the literature review. This was found to

be the major difference between the online communities and the e-learning

communities, as the e-learning participants have a specific purpose: to learn. For this

reason, the e-learners were given explicit guidelines on: netiquette, the use of

emoticons, how to write online messages based on results from this project’s

preliminary studies; and the structure of the collaborative e-learning episode (see

Appendix X).

On the question about collaboration with the Greek educational authorities everyone

agreed on the absence of communication channels (Graph 6.2.3-1):

Some times Very few times Never

The Greek educational authorities' communciation with participants

Pedagogical Institute (N=40)Ministry of Education (N=40)

13% 5%13%3%

Graph 6.2.3-1. Communication with the educational authorities

The communication channels with the educational authorities are not open as most

participants have never been contacted by the Pedagogical Institute or the Ministry of

Education (average 83%). Some participants (average 16.5%) were approached a

few times by either authorities.

Overall, only two young Greek teachers took part in this study; despite my efforts it

was impossible to find reports on the workforce so no assumptions can be derived

from this result. A reason for this lack of consideration of the age of employment

comes from Katsaros and Karageorgiou on their study on the absence of the Greeks

primary teachers training for the environment in their area between 2001-2006

(2006); the age range had three parameters: up to 40 years old (22 participants), 40-

50 (47 participants) and over 50 years old (21 participants).

The majority use the Internet regularly and have an active online life. However, basic

knowledge of the Internet as a tool for pedagogical activities, how to represent

themselves online as well as techniques to collaborate are all lacking. In addition, the

little communication with the Greek educational authorities implies lack of

participation in any major changes introduced in the Greek education system as

regards the use of ICT in education.

6.3 TRACING PARTICIPATION

Logging for e-learning environments provides a description of e-learners’

activities. Since particular modules to facilitate logging in Moodle do not exist, the

mdl_log file was extracted to create an Excel compatible Comma Separated Value

(CSV) file format. So logging will present a quantitative view on the frequency of

visits, as well as the number of active and passive participants. (My messages as the

observer participant in the study were not counted unless indicated otherwise. These

were general comments in Moodle@GSN and initiations to discussions in the

experimental environment.)

6.3.1 Frequency of Visits

This study targets participation in collaborative e-learning communities;

therefore, only the messages with at least one reply discussion depth were

considered appropriate for analysis. These messages were 175 from Moodle@GSN

(N=616) and 80 from the research pool (N=98); most other messages were either

announcements or members’ introductions without seeking a response from other

learners.

Views VS Posts: The activity in the two environments was (Table 6.3.1-1.):

Table 6.3.1-1. Moodle@GSN forums and users view log files

MOODLE@GSN LOGS (01/03-31/03/2007 – 31 days)

Type of Activity Activity Average per day

Percent on total views

1 User view 20,799 671 47.4 2 View individual discussion 12,193 393 27.7 3 View individual forum 7,666 247 17.4 4 View all users 1,597 51 3.6 5 View all forums 1,555 50 3.5 6 Add forum/post 175 6 0.4

Total 43,985 1,418 100

Almost double the clicks were related to viewing other e-learner’s profiles and then

discussions and forums (45.1%) whereas ‘forum add forum/post was limited’ (N=175,

0.4%). As stated before, this was deliberately encouraged so that the e-learners

could know more about each other before participation started (Table 6.3.1-2):

Table 6.3.1-2. Forums and users view log files in the research pool

RESEARCH POOL LOGS (25/03-31/04/2007 – 7 days)

Type of Activity Activity Average per day

Percent on total views

1 Forum view discussion 799 114 55.7 2 Forum view forum 427 61 29.2 3 View forums 86 12 5.8 4 Forum add forum/post 80 11 5.5 5 User view 39 6 2.8 6 User view all 30 4 2.0

Total 1,461 208 100.0

The logs related to forums (view discussion, view forum, and view forums) in the

research pool were of high priority (1,312 logs, 90.7%) whereas the users view was

limited (69 logs, 4.8%). This also means that the social reasons for passive

participation were almost eliminated at the beginning of the course.

Next, the total number of posts, and posts for analysis appeared as follows (the total

number of posts including my posts is in the parenthesis) (Table 6.3.1-3):

Table 6.3.1-3. Total number of posts

NUMBER OF POSTS

Frequency Percentage(N=714) Average per day

1 Moodle@GSN (31 days) 616(850) 86.3 19.8

Message for Analysis 175 24.5 5.6 2 Research pool

(7 days) 98 13.7 14

Message for Analysis 80 11.2 11.4 Total 714 23.0 (31 days)

Total for Analysis 255 35.7 8.2 (31 days)

The previous table presents that the overall average posting per day was 19.8

messages for Moodle@GSN and 13.6 for the research pool. From the overall 616

posts in Moodle@GSN, 175 (28.4%) were suitable for analysis, whereas from the 95

messages in the research pool, 80 (84.2%) were analysed. A comparison is

presented (Graph 6.3.1-1):

Comparison: Number of Messages & Messages for Analysis

11.2 11.4

Analysed Messages Percentage on totalnumber of messages

(N=714)

Average per Day(N=31)

Moodle@GSNExperimental Environment

Graph 6.3.1-1. Comparison between sent messages and messages for analysis

The number of selected messages for analysis is higher in Moodle@GSN: there

were 175 messages (24.5%) in Moodle@GSN and 80 (11.2%) in the research pool

with an average of 5.6 messages in Moodle@GSN and 11.4 messages in the

research pool posted per day. Active participation in Moodle@GSN was richer as

regards the discussion depth. However, the proposed tools and evaluation

techniques are suggested to be catalysts for active participation and collaborative e-

learning. It appears that about half of the messages were posted in the experimental

environment in a quarter of the time compared to Moodle@GSN.

Temporal View: A temporal overview of all activities can provide an in-depth view

(Table 6.3.1-4):

Table 6.3.1-4. Temporal overview of all activities

INTERVENTION & EVALUATION Observation Course DayCommunity Management Tools

Moodle@GSN 0 O0 Baseline 1 On date Until date

1 O1 01/03/2007 3,821 6,808 n/a 2 O2 03/03/2007 2,088 10,987 n/a 3 O3 07/03/2007 2,427 20,990 n/a 4 O4 14/03/2007 1,243 30,007 n/a 5 O5 22/03/2007 1,553 42,312 n/a 6 Baseline 2 On date Until date7 O6 26/03/2007 365 44,771 501 501 8 O7 30/03/2007 505 46,793 387 3,796 9 O8 31/03/2007 176 46,969 364 4,160 10 Baseline 3

The previous table presents that the number of all activities in Moodle@GSN is

decreased as the course progresses. From almost 4,000 activities on the first day of

the course, there were 176 activities in the end of the course. Posted messages

appear as follows (Table 6.3.1-5):

Table 6.3.1-5. Temporal overview of posted messages (add post/forum)

INTERVENTION & EVALUATION Observation Course DayCommunity Management Tools

Moodle@GSN 0 O0 Baseline 1 On date Until date

1 O1 01/03/2007 38 76 n/a 2 O2 03/03/2007 33 152 n/a 3 O3 07/03/2007 32 313 n/a 4 O4 14/03/2007 11 416 n/a 5 O5 22/03/2007 11 567 n/a 6 Baseline 2 On date Until date7 O6 26/03/2007 2 585 16 16 8 O7 30/03/2007 6 601 9 69 9 O8 31/03/2007 5 606 29 98 10 Baseline 3

Similar to activities, the posted messages decreased towards the end of the course

with some more messages in the research pool. There were 38 messages on the first

day of the course and 5 messages on the last day of the course in Moodle@GSN. As

the course continued in the research pool, there were 16 messages on the first day

and 29 messages on the last day of the course. A comparison between activity and

posted messages reveals the following (Graph 6.3.1-2):

Overall activity VS posting

3,8212,088 2,427

1,243 1,553866 892540

38 33 3211 11 18 15

10,000

Observation dates

ActivityPosted messages

Graph 6.3.1-2. Logs of overall activity VS posting

Activity was significantly decreasing whereas posting was slightly rising in the

research pool. In fact, the posts on the last day (34 messages) were almost as many

as on the first day of the course (38 messages). Because the messages were related

to each topic and were not on social networking (e.g. saying goodbye or staying in

touch after the course), it might indicate that the e-learners had acquired enough

knowledge to finish the course with a good rate of quality posts. Another explanation

may be the Hawthorn effect.

Overall, online community management was initially focused on enhancing individual

actions (one way of communication) and social relationships (interactions) in order to

increase the feeling of presence. Then it was focused on enhancing participation

quality. This seemed to work; the logs revealed more activity on viewing the profiles

during the first days of the course that were diminished in the end whereas posting

was relatively stable and the messages quality was increasing. Lastly, the next

section examines participation.

6.3.2 On Participation

This section discusses active and passive participation. The calculation of

active participants was conducted by counting the members who posted at least one

message.

6.3.2.1. Active & Passive Participants

An overview of participants’ active and passive participation shows (Table

6.3.2.1-1):

Table 6.3.2.1-1. Number of active and passive participants

NUMBER OF ACTIVE & PASSIVE PARTICIPANTS

Participants Percentage Active Passive

TotalActive Passive

Moodle@GSN 59 36 95 62.1 37.9 Participants in both 34 6 40 85.0 15.0 Research pool 26 14 40 65.0 35.0

From the 59 active participants in Moodle@GSN, 34 of them participated in the

research pool. Overall, there were 26 active participants in the research pool; as for

the participants in both environments there were about 20% (N=14) more active in

Moodle@GSN. The next sections will try to shed more light in understanding

differences in active and passive participation as mere calculation may not provide a

coherent view.

6.3.2.2. Active Participation Levels

There were two phases in determining active participation levels as the initial

calculation was found not to be practical on a large scale.

Active Participation Levels I: The levels of active participation were calculated

according to the proposed model on low, medium and high participation, based on

the total number of sent messages (Table 6.3.2.2-1):

Table 6.3.2.2-1. Active participation levels (Initial proposition)

A. LEVELS OF ACTIVE PARTICIPATION (TOTAL NUMBER OF POSTS) Active Participation Levels (%)

(posts) Percentage

Low (1-25%)

Medium (26-75%)

High (76-100%)

Total Posts

(1-154) (155-462) (463-616) Low Medium High

Moodle@GSN 616 616 100 (1-83) (84-250) (251-333) Low Medium High Participants 333 333 100 (1-24) (24-71) (72-95) Low Medium High Research pool 98 98 100

The previous table presents that the proposed model calculated on the total number

of sent messages was not functional on a large scale as all participants appeared to

be on the low activity level.

Active participation Levels II: A second attempt was made to calculate the

messages based on the highest respondent’s posts; as previously, the calculation

was anchored in the bell curve to determine low, medium and high participation

levels (Table 6.3.2.2-2):

Table 6.3.2.2-2. Active participation levels (Second proposition)

B. ACTIVE PARTICIPATION LEVELS (HIGHEST POSTER) Active Participation Levels

(% & highest participant’s posts) Percentage Highest Poster Low

(1-25%) (1-38)

Medium (26-75%) (39-76)

High (76-100%) (77-152)

Low Medium High Moodle@GSN

P52:152 32 participants

54(P58) 1

participant

152(P52)1

participant94.0 3.0 3.0

Highest Poster

Low (1-25%)

Medium (26-75%)

High (76-100%)

(10-12) Low Medium High

Research pool

P50: 12 16 participants

5 participants

5 participants 62.0 19.0 19.0

The second attempt provided better practical results, There were 32 low, 1 medium

and 1 active participants in Moodle@GSN, and 16 low, 5 medium and 5 high

participants in the research pool. The highest poster sent 152 messages in

Moodle@GSN (P52), and 12 posts in the research pool (P50). Both medium (P58)

and high (P52) participants were e-tutors in Moodle@GSN. However, P58 posted 1

message and P52 did not post any messages in the research pool. With 12 posts, e-

learner P50 was the highest poster in the research pool, whereas he was a low

activity poster in Moodle@GSN sending 14 messages. P50 posted almost the same

number of messages in 31 days at Moodle@GSN and in 6 days at the research pool.

This means that P50’s posting activity was accelerated from low to high activity in a

Overall, it appears that Moodle@GSN required significantly more e-tutoring than the

research pool and this was reflected in e-tutors and e-learners’ behaviour. Since

there was no e-tutoring in the research pool, active participation was e-learners

directed. Once more it appears that the initial ‘social’ kick on the participants and

instructional modifications to adjust e-learning behaviour to the new collaborative

tools worked. Lastly, the e-learner-generated text provided the context to some

participants to express themselves.

6.3.2.3. Passive Participation Levels

Calculation of passive participation was conducted on four levels (zero, low,

medium and high) based on the days of viewing; zero level is when a participant only

subscribed to the 2 environments and returned the 2 questionnaires; high passive

participation is when a participant appears to visit the course but never crossed the

threshold of participation. The course lasted 31 days; this means an average of 10

viewing days for each level. Tracking the exact hours and minutes spent on the

system was found to be extremely difficult. (There is a need to note that the graph for

the activity overview in Moodle was misleading, so all participants’ logs needed to be

checked and verified from the individual logs.) (Table 6.3.2.3-1):

Table 6.3.2.3-1. Passive Participation Levels

PASSIVE PARTICIPATION LEVELS (VIEWS IN DAYS)

Zero (0 days)

Low (1-10 days)

Medium (11-20 days)

High (-31 days) Total

P51: 0 P47: 3 daysP38: 7 daysP19: 3 daysP1: 4 days

Moodle@GSN (31 days, 6 participants, 15%)

P7: 8 days

Total 1 5 0 0 6 Percentage 17 83 0 0 100

Zero (0 days)

Low (1-2 days)

Medium (3-4 days)

High (5-7 days) Total

P51: 1 day P21: 7 days P56: 6 days P59: 2 days P40: 7 days P16: 1 day P49: 4 days P43: 3 days P19: 3 days P29: 2 daysP38: 2 days

Research pool (7 days, 9 participants, 22.5%)

P1: 2 days

Total 7 4 1 12 Percentage 0 59 33 8 100

There were 6 passive participants in Moodle@GSN (15%) in 31 days and 9

participants in the research pool in 7 days. P51 was the only participant who

remained in zero participation. All 5 of the Moodle@GSN e-learners remained on the

low level of passive participation (83%) whereas 7 (59%) were on low, 4 (33%) on

medium, and 1 on high passive participation. Overall, most participants were located

in low passive participation, not exceeding the 10 viewing days. There were different

passive participants in the two environments; P1, P19, P38, and P51 remained

passive in both environments (10%); 7 participants were active in Moodle@GSN

(17.5%); and 2 in the research pool (5%), these were the activated lurkers, this

means 33.3% of the passive participants. An overview of the activated passive

participants was as follows (Table 6.3.2.3-2):

Table 6.3.2.3-2. Posts from passive participants

PASSIVE PARTICIPANTS’ POSTING BEHAVIOUR To: Moodle@GSN To: Research pool

Participants Posts Participants Posts

P47: Low 1 From: Moodle@GSN

P7: High 1

P59: Low 1 P21: High 2 P43: Medium 2 P29: Low 3 P16: Low 3 P40: High 6 P49: Medium 11

From: Research pool

P56: High 25

There were 2 Moodle@GSN low and high passive participants who posted 1

message each in the research pool. There were 3 low, 2 medium and 3 high passive

participants who posted in Moodle@GSN but not in the research pool. The tendency

of passive and active participation can be depicted in Graph 6.3.2.3-1:

Graph 6.3.2.3-1. Active & Passive Participation locus from the same participants

The previous graph presents that low, medium and high level passive participants

remained in the same level of active participation. In other words, a person who

observes a lot of participation is highly likely to be an active participant in a different

forum provided favourable circumstances to the e-learner allow the change of

behaviour. It also depicts the idiosyncratic character of the individual as found in

Nonnecke and Preece (1999), and stresses the importance of investigating the space

between passive and active participation if more participation in the e-learning

communities is desirable. This gap was found as the sleeper effect in the literature

review (Chapter 2.2.1).

Because the result of the increased passive participation in the research pool was

unexpected, I contacted the passive participants and asked them why they did not

participate. It appears that there were different reasons. P1 complained that time was

limited for him (personal communication via email 27/03/2007). P38 said: “I had

extreme difficulty with communication, I did dedicate many hours to build my profile

and in the end I didn’t make it. I couldn’t participate in any of the videoconferences

due to the Internet connection. Once I was asked to prepare a text and I wrote about

the water. I did receive the newsletters from time to time explaining exactly what I

had to do; however, I couldn’t follow either because I couldn’t find the specific link or,

when I could find the link, I couldn’t get into the course and I was wondering in the

classes.” (Personal communication via email, 01/08/2007). Looking into P38’s first

questionnaire, it appears that she was using computers for 5 years; she was not

trained, and never worked with LMS. O1 quit because of GSN technical problems,

and he got scared of the environment and the immediate responses of co-learners;

he said he needed to follow at own pace. Although O2 also quit, he sent a message

addressed to me in Youtube and said the following: “Professional work, kindness,

positive thinking was beyond any expectations. I was proud to be a Greek teacher;

however, I was angry because the Greek educational community does not take

advantage of its talents and knowledge of technology in many fields.”.

P51 visited the research pool for one day and never looked at Moodle@GSN. P1,

P19, and P51 reported that they did not have any spare time. P49, an active

participant in Moodle@GSN, appeared to have serious login problems in the

research pool and the log showed continuous failed logins, I contacted her and tried

to solve the technical problem (28/03/2007). The online course was extended by one

week, the week of participation in the research pool was the week before Easter; this

meant that participants were preparing for Easter or as in the case of P16 were in

Europe on Comenius projects. These participants were not in fact passive. When the

participants were asked about the worst thing in the course, most said lack of time

(N=40, 12, 30%), technical problems (10, 25%), and being unable to participate as

much as they wanted (4, 10%). Overall, the main reasons were lack of knowledge

(both personal and technical) as to how to collaborate online (Table 2.3.2.2-1), and

perhaps this prevented the participants from engaging in the way they wanted.

This section discussed active and passive participation; the overall participation was

decreasing and increased slightly at the end of the course. Active and passive levels

of participation provided a technique for coherent and accurate measurement that

can be used by the e-tutors to support the e-learners. Furthermore, the messages for

analysis in the research pool were found to have more replies than the ones in

Moodle@GSN. One way or another, numeric analysis found inadequate for in-depth

messages analysis and as a means to determine their quality. This was however

feasible with the Collaborative e-Learning Episodes analysed in the next section.

6.4 THE COLLABORATIVE E-LEARNING

EPISODES

Messages analysis was used to determine the number and quality of the

Collaborative e-Learning Episodes (from now on CeLE) and aimed to:

• distinguish mere provision of information and collaborative e-learning

as one measure of e-learning quality;

• find correlations between passive - active participation and

collaborative e-learning;

• provide some evaluation towards the pedagogical usability and use of

the new collaborative tools; and

• evaluate the CeLE updated version.

The proposed CeLE analytical framework considers 4 variables, 3 quantitative and 1

qualitative. The quantitative variables are: richness of text, discussions depth, and

density. The CeLE structure as such is the qualitative variable. All messages from

both Moodle@GSN and the research pool were analysed. All images and Urls were

considered in the analysis and counted as one item. (My messages were not counted

unless indicated otherwise.)

6.4.1. Quantitative Variables

Comparison of the messages quantitative analysis in the two environments (see data in Appendix XI) led to the following results (Graph 6.4.1-1):

Correlations between Messages for Analysis, Richness of Text, & Discussion Depth

Introductio

n (01- 2

1/03/2

Timetable

(01 – 28/03

/2007)

Social n

etworking

(01-24/0

3/2007)

Moodle (01-0

8/03/2007)

Problems (01-0

8/05/200

Projects Arch

ive (0

1-07/03/200

Blogs (01-31/03/2007

Tools (0

3-12/03/2007)

Blog & HTML (0

5-12/03/200

Problems (

12-23/03/200

Design

(17-18

/03/2007)

Practica

lity (1

3-18/03/20

Groups

(18-24/03/20

Technic

al Problem

s (16-22/03/07

Groups (18-2

3/03/07)

Project ideas

(01-06/03/2007)

Other (01-1

8/03/2007)

News (

28-30/03/0

VC in E-le

arning

(28/03-0

1/04/07)

Subjects & Dates

Messages for AnalysisRichness of TextDiscussion Depth (Participants)Discussion Depth (E-Tutors)

Graph 6.4.1-1. Comparison between messages for analysis, richness of text, and discussion depth

Graph 6.4.1-1 provides a comparison between messages for analysis, richness of

text as well as the discussion depth related to both e-learners and all participants (e-

learners and e-tutors). Richness of text and discussion depth involved counting the

messages and the words included. All these variables were found to be interrelated;

in other words, when the text was rich, then there were more messages for analysis

this means having more than one replies and the higher the discussion depth.

Density was calculated with Fahy and colleagues’ density formula, 2a/N(N-1)

(a=interactions, N=number of participants). Messages density was almost double in

Moodle@GSN (0.19) compared with the research pool (0.1). However, Fahy’s

formula does not consider interaction time, and is highly sensitive to the size of the

group. Quantitative variables can give a specific picture of the research context;

however, there is a need to investigate its quality.

6.4.2. Qualitative Variables

E-learning quality in this study was measured by the Collaborative e-Learning

Episode (CeLE) analytical framework. A CeLE is an argumentation cycle with starting

points (social cues, information and questions), middle (explanations, explorations,

agreements, disagreements, and evaluations), and ending points (summaries, social

cues, and silence). A productive CeLE occurs when the participants introduce a new

idea. There were 255 messages suitable for analysis, 175 in Moodle@GSN and 80 in

the research pool. These messages were categorized and inserted in Atlas-ti™ in

order to find the messages that indicated at least one CeLE. The analysis suggested

thirteen CeLEs (Table 6.4.2-1):

Table 6.4.2-1: Collaborative E-Learning Episodes Overview

COLLABORATIVE E-LEARNING EPISODES

CeLEs in Moodle@GSN CeLEs Section Forum # Threads # Thread # Words

A Introduction 1 Introduction 58 I #18/ 10(3)-PX2 601(8)Total 5 2

II #25/ 8(1)-PX1 623(11)III #29/ 7(1)–P18 133(6)IV #46/ 5(1)-P2 276(93)V #50/ 18(2)-P52 1,782(82)

C Blogs 1 Blogs 61

VI #54/ 6(1)-P15 526(9)Total 3 1

CeLEs in the Research pool 1 News 8 VII #4/ 3-P13 725

VIII #3/ 18-R 2,213(9)IX #4/ 10-P37 882X #6/ 8-P50 941XI #7/ 22-R 3,990(86)XII #8/ 5-R 474(27)

G VC in E-Learning 2 VC in E-

learning 9

XIII #9/ 6-R 153(18)Total 2

It appears that in regard to Moodle@GSN, 1 CeLE was found in the introduction

forum, and 5 in the blogs discussion. Similarly, there was 1 CeLE in the news forum

and 6 in the videoconferencing discussion in the research pool. I initiated 4

discussions in the research pool and none in Moodle@GSN. P52 was also an e-

tutor; this means that the richest in words CeLEs were initiated by e-tutors.

CeLEs overview in the two environments is presented next in relation to individual

posters and duration in days (researcher’s posts in parentheses) (Table 6.4.2-2):

Table 6.4.2-2. Collaborative e-Learning Episodes selected for analysis

FINAL CeLEs Moodle@GSN

CeLE # # Individual Posters Dates Duration

(days) # Words

I 4(1) 01-05/03/2007 5 601(8) II 6(1) 06-06/03/2007 1 623(11) III 5(1) 05-05/03/2007 1 133(6) IV 5(1) 03-03/03/2007 1 276(93)

V 9(1) 18-22/11/2006 &25/02-02/03/2007 11 1,782(82)

VI 4(1) 28-28/02/2006 1 526(9) Total 3,941(209)

Research pool VII 3 27-29/03/2007 3 725 VIII 10(1) 21-31/03/2007 10 2,213(9) IX 7 29-31/03/2007 3 882 X 6 27-29/03/2007 3 941 XI 17(1) 26-29/03/2007 4 3,990(86) XII 5(1) 26-29/03/2007 4 474(27) XIII 4(1) 24-28/03/2007 5 153(18)

Total 9,378(140)

CeLEs in the research pool were more than twice as rich as in Moodle@GSN, with

3,941 words (30%) in Moodle@GSN and 9,378 words (70%) in the research pool. It

appears that the richest CeLEs last on average 4 days and in 2 occasions the richest

CeLEs were open 10 and 11 days rather than the average of 4 days. They become

richer as the course is unfolding related to the number of days and the number of

words. For example, the CeLE-I lasted 5 days and had 601 words; and more CeLEs

appeared towards the end of the course. It is interesting to note that there is a gap

after the first week; the CeLEs stopped on 06/03/2007 and appeared again on

18/03/2007. The CeLEs’ temporal overview is presented next (Table 6.4.2-3):

Table 6.4.2-3. Collaborative e-Learning Episodes temporal overview

INTERVENTION & EVALUATION Observation Course DayCeLE in Moodle@GSN Tools & CeLEs

0 O0 Baseline 1 1 O1 01/03/2007 n/a 2 O2 03/03/2007 n/a 3 O3 07/03/2007 I, II, III, IV n/a 4 O4 14/03/2007 n/a 5 O5 21/03/2007 V & VI n/a 6 O6 Baseline 2 7 O7 28/03/2007 VII, X, XI, XII, XIII 8 O8 31/03/2007 VIII, IX

Most of the Collaborative e-Learning Episodes in Moodle@GSN were technical

enquiries and most of the time the discussions were developed in small chunks. For

example CeLE III had three chunks of smaller enquiries that led to answers to

questions unfolding within the CeLE. The first four CeLEs were initiated in the first

week and then a 2 weeks gap appears. These first CeLEs were on getting to know

each other as well as technical problems; the last ones were of more quality. For

now, an overall comparison on duration in days, number of words, threads and

individual posters can also provide a posting timeline (Graph 6.4.2-1):

CeLEs: Comparison between Duration (days) and number of Words, Threads & Indivudual Posters

3 3 4 4 5

593 612

127 183

517 7252,204

882 941

10 8 7 5

1810 8

5 64 5 4 48

3 39 7 6

Duration 5 1 1 1 11 1 3 10 3 3 4 4 5

Words 593 612 127 183 1,700 517 725 2,204 882 941 3,904 447 135

Threads 10 8 7 5 18 6 3 18 10 8 22 5 6

Posters 4 5 4 4 8 3 3 9 7 6 16 4 3

CeLE-I CeLE-II CeLE-III CeLE-IV CeLE-V CeLE-VI CeLE-VII CeLE-VIII CeLE-IX CeLE-X CeLE-XI CeLE-XII CeLE-XIII

Graph 6.4.2-1. CeLEs factors’ comparison graph

The previous graph presents that there are interrelations between the factors in a

successful CeLE. Since a CeLE is related to co-creativity and new knowledge

construction, idea generation is found to be related to all factors. In other words,

when duration is in days, number of words, threads and individual posters reach a

peak, and idea generation reaches a peak.

However, the aim of collaborative e-learning is e-learners’ generated text; for this

reason the same analysis is presented with and without e-tutors’ contributions (Table

6.4.2-4):

Table 6.4.2-4. CeLEs: e-learners and e-tutors’ contributions

FINAL CeLEs Moodle@GSN

# Words CeLE # # E-learners – Unique # posts E-tutors Duration

(days) E-learners E-tutors 1 I 2 4 5 396 205 2 II 3 6 1 455 168 3 III 2 5 1 93 40 4 IV 2 5 1 192 84 5 V 5 9 11 726 1,056 6 VI 2 4 1 384 142

Total 2,246 1,695 Percentage 53% 47%

Research pool 7 VII 3 3 3 725 0 8 VIII 10 10 10 2,213 0 9 IX 5 7 3 715 167

10 X 5 6 3 905 36 11 XI 15 17 4 3,204 786 12 XII 5 5 4 474 0 13 XIII 4 4 5 153 0

Total 8,389 989 Percentage 89% 11%

It is evident that the e-learners were more active in the research pool. In

Moodle@GSN there were 2,246 words from the e-learners (53%) and 1,695 (47%)

from the e-tutors. As for the research pool, there were 8,389 words from the e-

learners (89%) and 989 (11%) words from the e-tutors. This difference is significant

as illustrated in the next graph (Graph 6.4.2-1):

Number of words posted in CeLEs by E-learners & E-tutors

1395989

1 2Moodle@GSN

E-learnersE-tutors

Experimental Environment

57% 43%

Graph 6.4.2-2. Comparison for number of words posted by

e-learners and e-tutors

The previous graph presents that the e-learners’ ratio of words in posting was

increased by 32% in the research pool CeLEs. To conclude the section on the

qualitative variable, 2 CeLEs were selected, from Moodle@GSN and the research

pool. The two environments were viewed as complementary so selection was based

on the most interesting and representative examples, one from each environment,

CeLE-III from Moodle@GSN and CeLE-IX from the research pool. CeLE-II and

CeLE-IX found to be similar as regards the number of words as well as the number of

e-learners and posters. In addition, CeLE-VIII seems to be interesting for

investigation since there were 10 messages sent by 10 different individuals, all being

low active participants. The last CeLE detailed analysis is presented in Appendix X

(A_X_1-4).

In summary, information exchange in CeLE III had a linear structure which unfolded

as a problem solving activity on a technical problem. On the other hand, CeLE IX did

not have a linear structure and referred to the use of specific e-learning tools in

building a project. In CeLE IX there were more agreements, disagreements,

arguments, and exploration of each other’s ideas. These were expressed both as

monologues as well as threaded dialogue. These processes can be seen as

knowledge internalisation and externalisation through monologue and dialogue which

promoted participants’ critical and creative thinking (Appendices A_X_5 and A_X_7).

As there was only one participant in a medium activity level and seven participants

on a low activity level, the appearance of these structures with the aid of previous

knowledge on collaborative e-learning and even the limited use of MessageTag may

be reasons for tackling passive participation (e.g. Klemm, 1998; Khine et al., 2003;

Jeong & Davidson-Shivers, 2006). The use of tools to reveal these structures even

on a limited level, can be indicated by the fact that previous knowledge existed in

Moodle@GSN; however, the CeLEs were not as rich, varied and consistent as in the

research pool. Knowing, viewing, and carefully using the collaborative e-learning

technique can give confidence to and encourage e-learners in their participation. It

appeared that there were transitions between internalisation and externalisation of

learning and this means that design should explicitly support dialogical sequences by

broadening and deepening this space.

6.5 THE SENSE OF E-LEARNING

COMMUNITY INDEX

The Sense of e-Learning Community Index (SeLCI) aims to provide in-depth

insights to human-human interactions within e-learning communities. The SeLCI

attributes are:

1. Community evolution: initial opinions on the community evolution, shared

interests and values, knowing about the community, new members’

contribution, and the collaborative tools;

2. Sense of belonging to the e-learning community;

3. Empathy as a representation of what co-learners know and feel; 4. Trust: knowledge exchange, help and support; and

5. Intensity: levels of passive and active participation, and persistence;

6. Collaborative e-learning quality: participants’ opinions, and the number of

collaborative e-learning episodes.

7. Social Network Analysis

o Global cohesion: density, reciprocity, cliques, and structural

equivalence;

o Global centrality: centrality degree, closeness and betweenness; and

o Local Real-Time Nodes and Centrality: tools results.

Quantitative, thematic, and social network analysis were employed within the

ethnotechnological framework to evaluate the SeLCI. As before, the questionnaires

from 40 participants (N=40) were analysed. The data for quantitative analysis were

inserted in the Statistical Package for the Social Sciences (SPSS 11.5) and Microsoft

Excel. Thematic analysis was conducted for the open questions and the collaborative

e-learning episodes using Atlas-ti™. Finally, social network analysis was aided by

UCINET (Borgatti et al., 2002).

The next sections will explore the SeLCI starting with the community evolution.

6.5.1 Community Evolution

The first SeLCI attribute is related to understanding the community evolution,

shared interests and values, knowing about the community, new members’

contribution, and the community roles.

Evolution: Almost all participants (n=38, 95%) thought that the community was

developing; 2 responses were N/A (not applicable) so there was not an opposing

opinion. As regards the time needed for community evolution, most of them (n=17,

42.5%) said it needs some time to develop: 2 weeks, 13 (32.5%) 1 week, 10 about 4-

5 days (10%) and the rest 6 (15%) 1-3 days. If collaborative e-learning started

developing after the first week, this means 1 to 2 weeks is necessary for developing

a community and collaborative e-learning where the sleeper effect is considered to

occur. In other words, the first week the participants explore and familiarise

themselves with the system and the other learners and make decisions upon passive

or active participation.

Participants were asked to suggest elements that showed community evolution on an

open question (Graph 6.5.1-1):

Community Evolution

0 2 4 6 8 10 12 14

Number of responses (N=62)

Increasing interactivity / help

Communication outside andafter the courseCommon interests / goals

Online communication

Affective elements

Quick familiarisation

Increasing number ofparticipants Communication – general

Collaborative atmosphere

E-learners’ participation inplanningSense of belonging

Personal messages /experiences / first nameNew colleagues

Photos

Visiting others’ web pages

Knew nobody initially

Participation quality / quantity

Graph 6.5.1-1. Community evolution elements

The previous graph presents that the most important community evolution elements

were the increasing participation based on mutual help (n=12, 19%) as well as

increasing communication outside and after the course (e.g. phone, SKYPE, blog,

Facebook; n=8, 13%); then shared goals and interests (n=7, 11%) communication

during the course (n=6, 10%); affective elements such as trust and support

(n=6,10%); the quick familiarisation with the e-learning environment (n=4, 6%), the

increasing number of participants (n=4, 6%); the level of communicative activities

(n=3, 5%); and from 2 responses (3%) the collaborative atmosphere, participation in

course planning as adjustment to particular circumstances, the sense of belonging

and expressions of familiarisation e.g. exchange of personal messages, experiences,

and address of e-learners by their first name (n=2, 3%). Other elements (1 response,

2%) were on meeting new colleagues, the number of photos in profiles, visiting each

other’s personal web pages and adding each other’s links, some people did not know

anyone initially, and the quantity and quality of participation.

When they were asked whether they would continue their collaboration outside the

course, 24 said yes (60%), nobody said no; however, there were 16 N/A and missing

responses (40%). Willingness to keep the community going was also evident on their

demand for a blog, a Facebook group be notified if a new course will start. However,

because this is not organised by GSN and the online course was part of this

research, so this request was not feasible.

The increasing interactivity and participation indicated that the community was an

evolving organic entity. This means that community evolution can be moderated by

supporting communication and participation in collaborative activities by helping e-

learners becoming passive and then active participants. For example, the use of

profiles and the initial social interactions to enhance trust and empathy supported e-

learners’ quick familiarisation with each other as well as with the LMS. Having

common targets and discovering similar interests creates a tendency known as self-

disclosure reciprocity as the participants exchange personal information and

experience (Wallace, 1999). The use of other communications means (e.g. phone,

SKYPE, blogs, and Facebook) other than the tools inside the e-learning system has

been found crucial for the community maintenance (Boase et al, 2006), and indicates

a healthy practice in this study. This may also suggest that different people have

different desires when it comes to communication modes.

Shared Interests & Values: Shared interest was found to be the third community

evolution element. Moreover, most participants replied to the closed question that

they had same interests (n=35, 87.5%), 2 denied (5%) and 2 were N/A (5%). Most

also said they had shared values (n=32, 80%), although 1 denied (2.5%) and 7 were

N/A (17.5%). Following the literature (e.g. Preece, 2000), shared values and interests

is the most important indicator to identify whether a community existed or not. In this

study these results were more than 80% which means that there was a strong

common ground from the participants’ viewpoint, an essential element for

Knowing the community: The participants said the following about the community

(Table 6.5.1-1):

Table 6.5.1-1. Knowing the community

1 2 3 4 5 THE COMMUNITY: Did you... Very

small Neither N/A

1 know the netiquette? 2 5 1 2.5 6 15 17 42.5 14 35

2 know the kind of community? 11 27.5 4 10 12 30 13 32.5

3 like working together? 2 5 5 12.5 17 42.5 16 40

4 express yourself freely? 5 12.5 5 12.5 15 37.5 14 35 1 2.5

5 participate actively? 6 15 7 17.5 8 20 13 32.5 6 15

6 think that the LMS helped the community?

5 12.5 14 35 21 52.5

7 think that the new tools helped the community?

5 12.5 13 32.5 20 50 2 5

The respondents liked working together (n=33, 82.5%) and were expressing

themselves freely (n=29, 72.5). The LMS provided the platform for the community to

exist (n=35, 87.5) and the new tools significantly helped in this process (n=33,

82.5%). Most of the participants thought that they knew about the netiquette (n=31,

77.5%) as well as the community (n=25, 62.5%). On freedom of expression the

results were lower (n=11, 27.5%) as well as active participation (n=7, 17.5%). Also,

half of the participants knew nobody before the course and the other half knew a few;

28 (70%) said they developed online relationships, 10 (25%) did not (2 were N/A).

Although the majority of the participants did not have experience in e-learning

communities and online collaboration, they were positive on collaboration and the

only thing that they were not happy about was not to be able to participate as much

as they wanted. Using tools in e-learning was important to them; knowing what the

community was about and developing relationships was a strong determinant in

SeLCI.

New members’ contributions: The results from the closed question on new

members’ contribution were in favour of new members: 34 (85%) supported their

contribution, 6 (15%) were N/A and nobody opposed. Thematic analysis on the e

open question also revealed the following (Graph 6.5.1-2):

Graph 6.5.1-2. New members’ contributions

The respondents believed that the new members can regenerate the community by

bringing new ideas (n=16, 24%) to share with the older members (n=9, 14%) via

active interaction and participation in the community (n=6, 9%). The most important

element is their enthusiasm (n=5, 8%). The participants believe that heterogeneous

groups function better (n=4, 6%) as they bring up questions (n=4, 6%). Other

responses refer to the need for training (n=3, 5%) and to keep the community going

(n=3, 5%); from two responses each (n=2, 3%) are freedom of expression, bringing

new perspectives and abilities into the community, provide feedback for older

members, whereas willingness to learn and collaborate is essential as well as the

use of new technologies. Shared interest, exploration with propositions and criticism,

quality and life-long learning are the last elements on new members’ contribution.

Moreover, P7 and P9 made interesting suggestions. P7 said that new members

‘…contribute their own knowledge that most experienced members can take

advantage of depending on e-learning targets. Based on their questions, more

experienced members can elaborate and analyse the coming data to transform the e-

learning context and future actions as interaction that can only bring positive results.’.

To P9, ‘old members can identify the new knowledge coming from newbies and help

in its transfer in positive ways’.

Additionally, two issues were revealed with regard to the new members in an e-

learning community. Despite the evidence on the importance of newcomers bringing

new ideas to regenerate the community, there was only one young participant in the

study; however, there were older newcomers. This means that the Greek teachers

even as newcomers have not recently graduated so there is a gap in their

professional training especially when there is a demand for faster training cycles in

recent years. In other words, the lack of training in the use of ICT in Education and

knowledge of collaborative techniques may be due to absence of teachers’ life-long

learning courses in Greece (Tsetsilas 2006). In addition, it is evident that new ideas

are of major importance to keep the community going; this is another collaborative e-

learning beneficial factor to community evolution.

Roles: The participants said that there were roles assigned to the members.

According to the closed question, 23 (57.5%) thought there were roles, 6 (15%) there

were not, and 11 (27.5%) thought there were no specific roles. However, thematic

analysis on the open question revealed the following (6.5.1-3):

Graph 6.5.1-3. Roles in the e-learning community

Participants’ responses were on community management, e-learning, and

participation. The moderator’s role was found important (n=7, 18%) along with

motivators (n=5, 14%) and leaders (n=4, 11%). There were also teachers (n=5,

14%), students (n=6, 17%), and technical support (n=2, 6%); active participants (n=2,

6%) and observers (n=1, 3%) were also included. Based on the assigned role of the

moderator and motivator, it appears that organisation of the community and e-

learning were of equal importance. As for the extent of provision of help that can

define roles between community members, 21 (52.5%) said that was neither great

nor small, 13 (32.5%) very great, 4 great (10%) and 2 (5%) to a small extent.

Overall, community management, e-learning and participation were themes for roles

which could be assigned. Equality in participation was also indicated by the fact that

e-tutoring and moderating was evident in Moodle@GSN and did not exist in the

research pool. In other words, the assignment of roles was not found to be a very

strong element in community evolution and collaborative e-learning.

6.5.2 Sense of Belonging

On the question of bonding or togetherness 16 respondents said it was strong

(47.5%); 18 said it was neither strong nor weak (45%); 1 said it was not strong

(2.5%); and 2 were N/A (5%). In the question on the factors that kept the community

together they said (N=40) (Graph 6.5.2-1):

Graph 6.5.2-1. Participants’ opinions on e-learning community elements

More than half of the participants (n=22) said that sharing the same goals and

interests was the main reason for holding the e-learning community together (n=22,

30%); then curiosity for new knowledge (n=12, 16%); and equally e-tutors (n=5, 7%)

and collaborative tools (n=5, 7%). More responses were: desire for success and

communication (n=4, 5%), willingness to participation, enthusiasm, participation as

such and effective learning (n=3, 4%), affective elements such as mutual help and

trust, the subject, collaborative learning for projects development and problem

solving (n=2, 3%). Other suggestions (n=1, 1%) were the immediate success and

feedback as well as reliability.

Furthermore, P11 believed that something that shows the sense of community is

active participation despite the technical problems; to P35 there was an ‘incredible

increase of active participation’; to P22, there was ‘willingness to collaborate beyond

and after the online course’, to P39 there was a ‘desire to keep the community going’,

and to P38 and P47 there was mutual help, understanding, and trust. P14 said that

concerning the use of profiles that the ‘photos created a climate of familiarisation with

each other and helped in developing a sense of belonging’.

Overall, it seems that the same factors that defined the sense of belonging are the

factors that contribute to the e-learning community evolution: shared interests and

values. Also, new knowledge is the collaborative e-learning outcome. The mediators

in this process are the e-tutors and the tools.

It is interesting to see an overview of the importance the participants applied to the

observed clusters grouped in three themes (Graph 6.5.2-2):

Correlations between Codes and Resposnes

Community Management(59%)

e-Learning (35%) Technology (6%)

Responses

(Percentage on codes)

Graph 6.5.2-2. Comparison of themes and community elements

Community management is considered the most important factor in this study (59%),

then e-learning (35%), and third the tools (6%). In other words, community

management facilitates community evolution and thus allows e-learning to take

place. Learning is an important element of community evolution and vice versa,

meditated by artefacts; in this case e-learning tools (Lave & Wenger 1991).

6.5.3 Empathy

Table 6.5.3-1. Empathy factors

EMPATHY FACTORS Know what Other was feeling when

reading a message

Feel what Other was feeling when reading

a message Action

EXTEND

Number Percent Number Percent Number Percent Very Small 1 2.5 2 5 11 27.5 Small 8 20 6 15 7 17.5 Neither 17 42.5 15 37.5 9 22.5 Great 13 32.5 15 37.5 11 27.5

Very Great 0 0 2 5 2 5 N/A 1 2.5 0 0 0 0 SD 0.9 0.9 1.3

Total 40 100 40 100 40 100 On the question of knowing what someone else was feeling (42.5%) replied they

more or less knew what the other person was feeling when reading a message and

13 (32.5%) they knew to a great extent; 8 (20%) said they knew to a small extent, 1

very small (2.5%) and one response (2.5%) was N/A. On “feeling what the Other was

feeling”, the responses were equally distributed between neither great or small and

great extent (n=15, 37.5%); 6 (15%) said they could feel other’s feeling to a small

extent, and equally 2 (5%) were on the very small and very great scale. As for

whether they took any action, 11 respondents (27.5) equally said to a very small and

great extent; 7 (17.5) to a small extent and 2 (5%) took action to a very great extent.

It appears that the results reach a peak in “knowing what the other person was

feeling”, they are more distributed on “feeling what the other person was feeling”, and

they reach a down peak in “action taking”. A scatter plot provided a more detailed

view (Graph 6.5.3-1):

Graph 6.5.3-1. Scatter plot for empathy

Convergence of the three empathy parameters when reading a poster’s message,

these are “knowing what Other was feeling”, “feeling what the Other was feeling” and

“action taking” seem to be on both a small extent and a great extent. Plotting

suggested a linear relationship between the three variables, so significance

evaluation was conducted with Pearson's Correlation Coefficient (Table 6.5.3-2):

Table 6.5.3-2. Correlations for Empathy factors

Correlations for Empathy Factors

Feel Other when reading

a message

Feel what Other was feeling

when reading a message

Action

Pearson Correlation 1 .489(**) .347(*)Know what Other was feeling when reading a message

Sig. (2-tailed) . .001 .028

Pearson Correlation .489(**) 1 .527(**)Feel what Other was feeling when reading a message

Sig. (2-tailed) .001 . .000

Pearson Correlation .347(*) .527(**) 1Action Sig. (2-tailed) .028 .000 .

N 40 40 40** Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed).

The strength of association between the three variables is positive but it does not

suggest a strong linear relationship. A moderate association (r=0.527) is between

“Feel what Other was feeling when reading a message” and “Action” with correlation

coefficient p≤0.01; “Feel Other” and “Action” association was the weakest (r=0.347)

with correlation coefficient p<0.05. Cronbach's alpha, as a coefficient of reliability and

consistency between the variables found α=0.698, which is on the limit of acceptance

in social research (0.70). Although empathy has been related to gaze and body

language (e.g. Lanzetta and Englis, 1989) it seems that it can occur online and it is

influenced by the properties of different communication media (Preece, 2004). It was

not possible to extract explicit relationships between the results of this study and

others as the frameworks for investigating online empathy were different. In this

study, the respondents appeared to know what the other person was feeling when

posting more than actually feel the poster. Nonetheless, in regard to action taking,

people may need time to actively participate in activities (the sleeper effect) before

consciously decide to work with others (the least collaborative effort).

There is a need to note that empathy has been related to the mirror neurons; this

means that the e-learners in their profiles provided information to the mirror neurons

to build representations of the other learners and their actions (Goleman, 2007).

However, investigation of such correlations was not part of this study.

6.5.4 Trust

The participants responded to statements on trust (Table 6.5.4-1):

Table 6.5.4-1. Trust levels

Statements Yes Percent No Percent N/A Percent

1 I can trust most of the participants. 37 92.5 1 2.5 2 5

2 I have to be very careful as some take advantage of others. 37 92.5 3 7.5

3 Most are trying to help. 38 95 2 54 Nobody can trust anyone else. 38 95 2 5

The contradictory closed questions on trust suggest high level of participants’

reliability; the majority (over 90%) responded that they could trust the other learners

as most were trying to help. So trust was evident to a significant extent. More

specifically (Table 6.5.4-2):

Table 6.5.4-2. Trust development towards individuals

1 2 3 4 5 TRUST Very

small Small Neither Great Very great N/A

1 Individuals who had a similar specialisation

11 27.5 16 40 12 30 1 2.5

2 Individuals who had similar writing skills 12 30 16 40 12 30

3 E-tutors 1 2.5 9 22.5 30 75

4 Experienced individuals 9 22.5 16 40 15 37.5

5 You can’t trust anyone 32 80 6 15 1 2.5 1 2.5

It appears that most of the participants could trust other e-learners with a similar

specialisation to a great (n=16, 40%) and very great extent (n=12, 30%) whereas 11

(27.5%) could trust them more or less; as for individuals who had similar writing

skills, the results indicate trust to a great (n=16, 40%) and very great extent (n=12,

30%) whereas 12 (30%) could trust them more or less. The results on trusting the e-

tutors were the most positive with 39 (97.5%) to trust them on a great or very great

extend and 1 neither a small or a great extent (2.5%). As for trusting the experienced

individuals the results were: 16 (40%) to a great extend, 15 to a very great extent

(37.5%) and 9 (22.5) neither small or great extent. The question to ensure that the

participants did not respond randomly revealed that the majority (n=32, 80%) could

trust other people.

Lastly, all but 1 participants reported that the level of trust had risen (n=39, 97.5%).

Almost all participants felt that they could trust the e-tutors and their co-learners.

Trust has been reported to be related to different forms of awareness, such as

personal information, presence on the community, demographic backgrounds,

capabilities and skills in performing specific tasks (Daniel, 2007:124). Trust is also

related to the mental models people develop when they first meet as well as the

content of their conversation and tend to develop very quickly (Norman, 1988).

However, these suggestions were not explicitly investigated in this study; here, trust

was linked to reciprocity and levels of participation to allow participants to work freely

together, evident in the freedom of expression to a great extent (n=29, 72.5%).

6.5.5 Intensity

Intensity refers to the participation levels and persistence; the latter is the

level to which participants pursue topics.

Participation Levels: Active and passive participation levels were found to vary in

the two environments. Seeing these levels as a process from low passive to high

active provides a different overview for intensity (Graph 6.5.5-1):

Passive & Active Participation Process

Zero Low PassiveParticipation

MediumPassive

Participation

High PassiveParticipation

Low ActiveParticipation

MediumActive

Participation

High ActiveParticipation

A: Moodle@GSNB: Research Pool

Graph 6.5.5-1. Passive & Active Participation Process

Line A corresponds to Moodle@GSN and is interrupted; the participants were located

in zero and low passive participation, high low active participation and one e-learner

in medium and active participation. As described in the previous sections, this may

be because medium and high activity users were e-tutors whereas there were no e-

tutors in the research pool. Line B corresponds to the research pool and seems more

broadly distributed showing higher activity than Line A. In other words, from an

activity viewpoint, intensity in the research pool seemed to be in greater balance.

Lastly, it is evident that participation increased from passive to active levels on a

social and temporal basis.

Persistence: The intensity element of persistence is the level to which participants

pursue topics in order to evaluate the emergence of a clear focus. Persistence was

located on two levels, discussion topic and thread. (Note that the e-tutors used the

‘split forum’ facility to facilitate the flow of the conversation and intervened in the

persistence ratio in a positive manner.) Both the number of initiations and replies with

more than two messages were calculated (Table 6.5.5-2):

Table 6.5.5-2. Persistence in Moodle@GSN

PERSISTENCE IN MOODLE@GSN Depth of persistence

Section Forums Forums Messages

Introduction (01- 21/03/2007) 43/49 66/231Timetable (01 – 28/03/2007) 7/7 127/127Social networking (01-24/03/2007) 1/1 30/30Moodle (01-08/03/2007) 2/2 7/7

A Introduction

Problems (01-08/05/2003) 6/22 117/127 Total 5 59/81 347/522

B Project Management Projects Archive (01-07/03/2007) 1/1 6/6

Total 1 1/1 6/6Blogs (01-31/03/2007) 42/43 187/198Tools (03-12/03/2007) 3/3 9/10C Blogs Blog & HTML (05-12/03/2007) 1/1 3/3

Total 3 46/47 199/211Problems (12-23/03/2007) 9/9 37/37Design (17-18/03/2007) 0/2 0/6Practicality (13-18/03/2007) 2/2 10/18

D Wikis

Groups (18-24/03/2007) 6/7 31/31 Total 4 17/20 78/92

Technical Problems (16-22/03/07) 1 12/12E Videoconferencing Groups (18-23/03/07) 1 16/16 Total 2 2/2 28/28

F Internet Cafe Project ideas (01-06/03/2007) 1/1 3/3

Other (01-18/03/2007) 2/2 6/6Total 2 3/3 9/9

Overall 16 128/154 667/868Overall Percentage 83.1 76.8

Average Percentage 80 The previous table presents that 59 out of 81 forums and 347 out of 522 messages

were following the subject of discussion in the introductory section; in the project all

messages were on topic these are 1 out of 1 forums and 6 out of six messages; in

blogs, persistence was strong as 46 out of 47 forums and 199 out of 211 messages

were on topic; in wikis the persistence depth was 17 out of 20 in forums and 78 out of

92 for messages; as in videoconferencing persistence was 100%, 2 in 2 forums and

28 out of 28 messages; the same rate appeared in the internet café with 3 in 3

forums and 9 out of 9 messages. The forums overall percentage was 83.1% with 128

out of 154 forums persistence depth which meant that the forums were relevant to

the forum topics. Slightly lower was the messages overall percentage (76.8%) with

667 out of 868 messages to follow the discussion topic. The overall persistence

depth in Moodle@GSN was 80%.

More persistence was observed in messages with 2-3 replies. As for the rest of the

messages, there were a small number of them irrelevant to the topic, sometimes

coming from the same e-learner; for example, 5 out of 6 irrelevant messages in the

‘Problems’ forum came from P48; they were events announcements. (Note that there

were no members’ announcements area in the online course.) Both forums on ‘wiki

design’ were irrelevant; this perhaps was because of the title forum: ‘What are the

main characteristics in wiki design? the goal to match, to serve the audience, both or

something else?’ As for levels of persistence in replies, the persistence depth was

found to be relevant to the thread depth; in other words, the more the replies the

more the probability of lack of persistence. Some times there was a reason for

shifting the discussion focus; for example, in Wiki topic, the focus was shifted in the

practicality discussion when one of the members found to have posted in another

person’s wiki without realising it (Reply 5): “Hi O3, I am P50; without doing it

intentionally, you created a webpage post in my wiki…”. Two similar changes of

focus occurred in the blog/blogs discussion when a problem on the suggested url

appeared and 5 messages were on finding the correct url. Lastly, a large number of

forums indicated a small number of replies so the level of persistence was maximum

for these forums. Overall, shift of focus was justified.

Similar results on persistence appear in the research pool (Table 6.5.5-3):

Table 6.5.5-3. Persistence in the research pool

PERSISTENCE IN MOODLE@GSN Depth of persistence

Section Forums Forums Replies

News (28-30/03/07) 2/2 5/5A Introduction VC in E-learning (28/03-01/04/07) 8/8 63/70

Total 2 10/10 68/75Percentage 100 90.6

Average 95.3

The forums had 100% persistence; with 10 out of 10 messages following the topic.

As for the messages, there were 68 out of 75 messages exhibiting persistence, with

90.6% percentage. The overall persistence in the research pool was 95.3%. In depth

analysis revealed that the discussion on re-using videos in a project in the

videoconferencing forum produced 21 replies; however, after the 13th reply the focus

changed to how the Ministry of Education supports the teachers on the projects and

what happens when the project finishes. Then the focus shifted to the Greek

education system and teachers’ training, and the last two messages partly brought

the focus back to the use of tools in projects.

More intensity found in the research pool: the process of participation was more

stable and coherent, and there was an overall persistence of 95.3% comparing to

80% in Moodle@GSN even though the number of messages was low.

Intensity appeared to be higher in the research pool: the participation levels were

more coherent and stable in the research pool having all levels from low passive to

high active participation; and persistence was found 90.6%. It appears that initial

online dialogical argumentation lacked depth and was redundant as participants

failed to sustain interaction, also found to be evident in the research by Khine and

colleagues (2003); as the participants gained knowledge and experience of

collaborative techniques based on information provision and observation of the e-

tutors, their behaviour changed in the research pool. It is interesting to note that for 3

years there were 19 messages with 1 one reply, whereas 1 message produces 27

replies (Chapter 4.3.1.2). Intensity also provides evidence for establishing common

ground. This is done by checking whether a conversation partner has heard and

correctly understood what is being said (Preece & Maloney-Krichmar, 2003). Lastly, it

is evident that intensity can depict any imbalance or equilibrium between passive and

active participation and a level of persistence as a SeLCI determinant.

6.5.6 E-Learning Quality

The Collaborative e-Learning Episodes analysis provided a qualitative view in

online discussions, aiming to assess quality in e-learning interactions. There were 13

Collaborative e-Learning Episodes, 6 in Moodle@GSN and 7 in the research pool.

However, it was considered important to acquire the e-learners’ viewpoint: whether or

not the e-learners asked for help and who helped them the most; if the e-learners

learned to collaborate; how they worked together; and to determine how the tools

aided their learning.

The respondents said that they asked help from the e-tutors (n=37, 92.5%) and less

from their co-learners (n=3, 7.5%). The majority replied that they actually learned

ways for collaborative learning (n=37, 92.5%), 1 did not (2.5%), and 2 N/A (5%).

More specifically, they suggested ways to achieve collaborative e-learning (N=41;

one participant provided more than one suggestion) (Graph 6.5.6-1):

Collaborative e-Learning

0 2 4 6 8 10 12

Number of responses (N=41)

Information & knowledgeexchangeCollaborative activities

Dialogue development

Mobility of ideas

Learn to communicate

Vicarious learning

New skills acquisition

Number of created projects

Graph 6.5.6-1. Elements that show community evolution: e-learning

Information and knowledge exchange were the most important factors for

collaborative e-learning (37%); then collaborative activities (27%), dialogue

development (17%), and mobility of ideas (7%). One suggestion each (3%) referred

to learning to communicate, vicarious learning, new skills acquisition, and the number

of created projects. Only 5 responses were on tools, 4 on the new collaborative tools

(80%) and 1 on profiles (20%). It appears that mere information was essential to

trigger collaboration but it was the collaborative techniques and the use of tools that

transformed information to collaborative e-learning by supporting different learning

styles. This result indicates that progressive discourse can be the outcome of

increasing participation in collaborative e-learning communities.

The next graph shows more specific opinions with regard to whom they learned from

(Graph 6.5.6-3):

Whom did you learn from? (N=35)

30, 56%17, 32%

3, 6%3, 6%

E-tutors

Otherlearners

More experienced learners

Own work

Graph 6.5.6-3. The e-learning facilitators

The previous graph presents that the participants learnt from the e-tutors (n=30,

56%), other learners (n=17, 32%) and equally more experienced learners (n=3, 6%)

and on their own (n=3, 6%). It appears that passive participation and vicarious

learning was one of the learning styles; P21 also said that she was ‘watching how

other people were working’. This result is in agreement with the centrality scores and

the responses on passive participants.

Overall, thematic analysis pointed at three themes, community management, e-

learning and technology (Graph 6.5.6-2):

Collaborative e-Learning

Community Management(63%)

e-Learning (30%) Technology (7%)

CodesResponses

(Percentage on codes)

Graph 6.5.6-2. Correlations between codes on collaborative e-learning quality

The importance attached to the factors on collaborative e-learning quality is in favour

of community management, then e-learning and finally, technology is the last one. It

is interesting to see that this attached importance is even higher for collaborative e-

learning than e-learning community (see Graph 6.5.2-2): the percentage is increased

as regards community management (63% from 59%), decreases for e-learning (30%

from 35%), and slightly increases for technology (7% from 6%). These results stress

the importance of the social aspect of collaborative e-learning.

Overall, quality in collaborative e-learning can be a Sense of e-Learning Community

Index (SeLCI) attribute as it provides a clear indication of quality in textual online

interaction by the number of collaborative e-learning episodes and participants’

viewpoint on their learning. Three distinct learning styles were revealed, instructional,

collaborative and vicarious learning. As before, community management was the

most important job for the e-tutors, then e-learning activities and lastly, the

technology. Some results can be triangulated by social network analysis in order to

provide a different viewpoint towards SeLCI. These will be discussed in the next

section.

6.5.7 Global Social Network Analysis

Social Network Analysis (SNA) can describe Greek teachers’ interactions as

well as triangulating previous findings. This is feasible because the relationships

based on text and words only have limited capacity to represent the social network;

in other words, photos provide a different view of a group of people than the script of

what they said. SNA focuses on global (found also as complete or group) and ego

networks. Global cohesion and centrality were investigated using UCINET (Borgatti

et al., 2002); cohesion can represent the interactions’ weight (density), participants’

preferences (reciprocity), any small groups (cliques), and similar behaviour (structural

equivalence); centrality can depict interaction direction (in-out degree centrality),

speed (closeness), and control (betweenness).

Two adjacency matrices were produced one 64*64 for GSN (Figure 6.5.5-1) that

included the main participants and others who had been interacting but not on a

regular basis and did not fit the criteria of participants’ selection. Also another 41*41

matrix was produced for the research pool that included my interactions (Valued links

and passive participants zeros are depicted; all other zeros were eliminated to make

the matrix more legible) (Figure 6.5.7-1):

Figure 6.5.7-1. GSN adjacency matrix in UCINET

Several problems occurred in producing the matrices: one was the discrepancy

between the system reply and the actual address of reply and the other was the

participation of two e-tutors and myself. First, the function ‘Reply’ in Moodle was

referred to the previous message whereas the actual reply could be addressed to

one or more e-learners sometimes higher up the forum. So in this study, where

apparent, the input in SNA was the actual addressed reply as conceived from the

message rather than as depicted on the system; this indicated a limitation in the

forum application in Moodle. For example, someone may send a post later in the

week by replying to the last message; however, the message may have been

addressed to somebody else. Messages that were replied to everyone as when the

participants were introducing themselves were linked to themselves on the adjacency

matrix. Then, two new sets of adjacency matrices were analysed, one with the

researcher and the 2 e-tutors as the most active participants in GSN, and one without

the 3 actors, these were two 38*38 matrices. This decision was made because this

study focuses more on collaborative e-learning for e-learners-generated text rather

than the e-tutors-generated-text.

6.5.7.1. Global Cohesion

The level of global cohesion was measured by assessing network density,

reciprocity, cliques, and structural equivalence. Density is the proportion of possible

links in network as it is the ratio of the number of links present in the network, to the

maximum possible links. Density was evaluated by the adjacency connection reports

in UCINET (Table 6.5.7.1-1):

Table 6.5.7.1-1. Group Network Cohesion: Density & Reciprocity

GROUP NETWORK COHESION: DENSITY & RECIPROCITY

GSN Research Pool All E-learners All E-learners

Total nodes 698 122 81 73 Density (matrix average) 1.0872 0.0256 0.0470 0.0418 Standard deviation 2.0167 0.1819 0.2376 0.2226 Reciprocity (Hybrid) 0.3618 0.2222 0.1852 0.2174

E-learners’ density is rather low, 0.0256 in Moodle@GSN, however stable in the

research pool (0.0418). This means that 2.6% in Moodle@GSN and 4.7% in the

research pool of all possible links were present; however, there was an increase in

density. The participants actually recognised their limited participation; they said they

were not as active as they wanted to be. In addition, the 2 highest posters in

Moodle@GSN influenced the groups’ density level; this means that the actual

increase in participation was almost doubled (0.0418 - 0.0256= 0.0162). This was

also evident in the collaborative e-learning episodes text richness, as it was doubled

in the research pool (see Table 6.4.2-2).

Reciprocity in SNA is the number of ties that are involved in reciprocal relations

relative to the total number of actual ties (Hanneman & Riddle, 2005). Reciprocity

appears higher within the e-learners (Graph 6.5.7.1-1):

(a) (b)

Graph 6.5.7.1-1. Reciprocal ties in GSN (a) & the research pool (b)

There were 4 reciprocal ties in GSN (28.6%) and 10 (71.4%) in the research pool.

However, due to the e-tutors role in GSN, it appears more as an evolutionary

process.

The increase of reciprocal ties is another indication of evolution in discussion from

monological to dialogical sequences between two participants. Strong and weak

reciprocal ties can also define strong or weak relationships within an e-learning

community. Therefore, reciprocal ties can maintain a strong social network; thus,

they are important for knowledge exchange and community knowledge building as it

means members’ constant by give and take within a community (Preece, 2004).

Reciprocity is also related to the social exchange theory (Blau, 1964); it posits that

individuals engage in social interaction based on expectations or the benefits active

participants can get from active participation, for example some sort of personal gain

or status. However, reciprocity can also be triggered by intangible returns in the

forms of intrinsic satisfaction and self-actualisation (Äkkinen, 2005). Based on

participants’ opinions for feeling guilty because of inadequate participation in the

course as well as their initial voluntary involvement in the GSN courses, it appears

that their target was learning, and thus, only implicitly related to the social exchange

theory. This also means that social loafing was not evident in this study as they

rather had shared interests and values.

A clique is a subgroup, a set of actors with each being connected to each other as a

maximal complete subgraph of three or more nodes (members) adjacent to each

other and there are no other nodes in the network that are also adjacent to all of the

members of the clique (Laghos, 2007). Cliques may overlap, that is a forum member

(node) can be a member of more than one clique (Bock & Husain, 1950). The results

presented in the following table are cumulative and refer to cliques created by 3, 4, 5

and 6 participants (Table 6.5.7.1-2):

Table 6.5.7.1-2. Cliques

CLIQUES

Moodle@GSN Research Pool Minimum set size

of participants All E-learners All E-learners

6 2 0 0 0 5 33 0 0 0 4 58 0 2 1

3 68 4 15 12

Most cliques were created by 3 participants in both environments. The e-tutors

dominated the cliques gathering up to 6 participants. The cliques were developed

without any intervention by any of the participants, e-tutors or myself. It is interesting

to note that the top scorers had inter-clique connections. When the cliques increase,

the social network remains active and thriving, especially if e-learners interact with

other e-learners who did not appear in a clique before; these are the activated

lurkers. In other words, the absence of cliques could have indicated a lack of

clustering that would have reflected the prevalence of weak ties.

As most the participants did not know each other before the study and were more

skilled in the research environment, the cliques were the glue for forums. However,

what fostered the cliques was not investigated in this study.

Structural equivalence describes the actors who have similar patterns of relations

to others in the network and exhibit similar communication behaviour. It presents a

different clustering view within a human network. Equivalence is important for

generalizations about social behavior and social structure; actors must not be

thought about as unique persons, but as examples of categories (sets of actors) who

are in some way, "equivalent” (Hanneman, 2001).

Two actors (nodes) are said to be structurally equivalent if they have identical ties

with themselves, each other and all other vertices (de Nooy et al., 2005). It is

computed by the Euclidean distance of tie-value from and to all other nodes (Lorrain

& White, 1971). The CONCOR technique (CONvergence of iterated CORrelations;

White et al., 1976) uses dendrogrammes (tree-diagrammes) for hierarchical

clustering whereas other techniques use algorithms to calculate network members’

individual behaviour (e.g. Everett & Borgatti, 1993). The CONCOR technique

calculates Pearson’s correlation coefficient between columns and depicts whether

two nodes are structurally equivalent if the corresponding rows and columns of the

adjacency matrix are identical. So the degree to which two nodes are structurally

equivalent can be evaluated by measuring the degree to which their columns are

identical. CONCOR is a divisive top-down clustering technique; it begins with one

group and then divides it up so the dendrogramme looks like an inverted tree. This

structure is calculated and thus artificial, resulting in failing to identify observed

clusters.

Interpretation of dendrogrammes for network clustering is as follows: the labels of the

actors are given on the left in UCINET; the network positions appear as lines; the

numbers at the top are the clustering levels, indicating the number of clusters at the

level of sharing at least 3 ties; the column in the middle is the row number in the

UCINET matrix for the network. (Dividing clusters of 3 or less individuals is not

preferable as correlations get very unstable) (Graph 6.5.7.1-2):

Graph 6.5.7.1-2. Structural equivalence dendrogrammes in GSN (all)

If each line represents a participant, the CONCOR dendrogramme reveals 7 splits on

the first level and 2 splits on a second level with four actors participating in all groups.

This means that 7 and out of them 3 actors had exhibited similar behaviour (Graph

6.5.7.1-3):

Graph 6.5.7.1-3. Structural equivalence dendrogrammes in the research pool (all)

In the research pool 3 participants were active in 2 second level groups and 5 first

level groups. The next CONCOR dendrogramme reveals 7 first and 4 second level

participants (Graph 6.5.7.1-4):

Graph 6.5.7.1-4. Structural equivalence dendrogramme in GSN (e-learners)

Here, the ties are less than the one with the researcher and the 2 high participation

e-tutors, however, the overall structure of the groups remain the same. Lastly, the

next dendrogramme refers to the e-learners in the research pool (Graph 6.5.7.1-5):

Graph 6.5.7.1-5. Structural equivalence dendrogramme

in the research pool (e-learners)

This graph reveals 5 first and 2 second level multi-actor positions with one solo-actor

position.

In conclusion, if grouping actors with equivalent behaviour, the results from the

previous dendrogrammes appear as follows (Table 6.5.7.1-3):

Table 6.5.7.1-3. Equivalent e-learners

EQUIVALENT E-LEARNERS

Moodle@GSN Research Pool All E-learners All E-learners

1st level 7 7 5 52nd level 3 4 3 2

Structural equivalence seems to be steady in the two e-learning environments. There

were 7 and 5 participants with first level equivalence in the two research pools. There

was one more e-learner with second level equivalence if e-tutors were excluded (4-

3=1) whereas it was the opposite situation in the research pool with one less e-

learner (3-2=1). In other words, more e-learners were imitating e-tutors’ and other e-

learners’ behaviour, and thus passive behaviour was decreasing. This was in

accordance to participants’ comments on watching what the e-tutors were doing and

learning vicariously. This means that observation had a positive effect in replicating

behaviour active participation especially if the participants did not have previous

knowledge of working and learning online.

Overall, the social network analysis attributes of the Sense of e-Learning Community

Index (SeLCI) indicated that the interactions’ weight (density) was doubled in the

research pool; participants’ preferences (reciprocity) were also significantly

increased; more similar behaviours (structural equivalence) were observed in

Moodle@GSN rather than the research pool; and there were some small groups

(cliques) that remained almost the same throughout the study.

6.5.7.2. Global Centrality

Global centrality investigates the communication nodes between the

members of a network and is characterised by direction and strength and refers to

out-degree centrality (replies made), in-degree centrality (received messages) as well

as group in and out closeness and betweenness.

Centrality is measured by the portion of nodes that are adjacent to each node, the

sum of each row in the adjacency matrix representing the network. The centrality

scores were (Table 6.5.7.2-1):

Table 6.5.7.2-1. Group Centrality

GROUP CENTRALITY SCORES

Network Centralization (Out-Degree) 13.852% 10.826% 8.606% 9.372%Mean 8.328 0.974 1.667 1.590 Standard deviation 20.321 2.154 2.316 2.250 Network Centralization (In-Degree) 10.751% 5.425% 6.940% 6.671%Mean 8.328 0.974 1.667 1.590 Standard deviation 13.999 1.459 2.089 1.983 In-closeness (Network in-Centralization) 73.97% 32.68% 49.49% 49.83%Mean 20.581 1.447 5.885 5.565 Standard deviation 10.762 1.859 5.147 4.919 Out-closeness (Network out-Centralization) 78.30% 55.04% 42.74% 42.53%Mean 20.581 1.447 5.885 5.565 Standard deviation 11.387 2.532 5.088 4.626

Betweenness (top 3 participants) 32.7I (R)

18.7(P52)5(P24)

2(P32)1.7 (P24)0.9(P37)

16.2(P50) 11 (P18)

6.7 (P24)

16.2 (P50) 11.8 (P18) 7.3 (P24)

Mean 1.254 0.173 1.751 1.950 Standard deviation 4.655 0.431 3.235 3.436 *Data matrix dichotomized for closeness, such that Xij > 0 was recoded to 1

Degree centrality refers to a directed network (where the direction of the

communication is important); the in-degree centrality is the portion of nodes that are

adjacent to each node, and out-degree centrality is the portion of nodes that are

adjacent from each node (Freeman, 1979). Even though Borgatti (2005:70) suggests

that Freeman’s centrality has been misapplied, it is widely used because there are no

other suggestions for coherent results on global centrality. The nodes with the

highest degree scores are the ones which are more central (powerful) in the network.

Degree centrality was preferred rather than eigenvector centrality as a measure of

immediate influence - the ability to influence others directly or in one time period

(Borgatti, 2005:70). This was because the subject of investigation was the levels of

activity and thus the centrality and peripherality degree of the members.

In this study, the e-tutors’ role was apparent in Moodle@GSN. For the e-tutors the

scores were: out-degree=13.852% (SD=20.321), in-degree=73.97% (SD=13.99). For

the e-learners the scores were very limited: out-degree=10.826% (SD=2.154), in-

degree=5.425 (SD=1.459). The e-learners had more stable scores in the research

pool; with the e-tutors the scores were: out-degree=8.606% (SD=2.316), in-

degree=49.49% (SD=2.089); without the e-tutors the scores were: out-

degree=9.372% (SD=2250), in-degree=6.671% (SD=1.983).

The out- and in- degree centrality appear to have great differences depicted mostly in

the standard deviation rather than centrality itself. Standard deviation dropped in the

e-learners centrality scores in the research pool which means that the differences

between the e-learners were diminishing. There was an increase in in-degree

centrality and a decrease in out-degree centrality. This means that the e-tutors had

the power in the information flow in GSN and the e-learners in the research pool in a

more distributed manner. In a more in depth analysis, the top 10 centrality scorers in

out- and in- degree centrality (Table 6.5.7.2-2) were:

Table 6.5.7.2-2. Top 10 Scorers in Out-Degree Centrality

OUT-DEGREE CENTRALITY: TOP 10

Participant Out-Degree Participant Out-

Degree Participant Out-Degree Participant Out-

Degree1 P52 120 P32 13 P50 12 P50 122 R 108 P18 4 P22 6 P18 63 P58 47 P48 3 P18 6 P22 5

4 P18 25 P37 2 P14 4 P48 4

5 P37 20 P24 2 P48 4 P37 3

6 P32 19 P9 2 P37 4 P24 3

7 O2 13 P13 1 P6 4 P14 3

8 P56 10 P2 1 P2 3 P6 3

9 O4 9 P50 1 P12 3 P12 3

10 O9 9 P6 1 P13 3 P13 2

If the 3 e-tutors (P52, R, and P58) are omitted, the next 3 active participants appear

first in out-degree centrality (sent messages) in GSN. P18 and P37 from GSN appear

to be among the top scorers in the research pool. The top scorers for in-degree

centrality were (Table 6.5.7.2-3):

Table 6.5.7.2-3. Top 10 Scorers in In-Degree Centrality

IN-DEGREE CENTRALITY: TOP 10

GSN Research Pool All E-learners All E-learners Participant In-

Degree Participant In-Degree Participant In-

Degree Participant In-Degree

1 R 95 P9 7 P50 10 P50 9 2 P52 52 P24 4 P18 5 P18 5

3 P37 31 P13 4 P37 5 P37 5

4 P9 25 P18 3 P24 5 P24 5

5 P18 19 P37 3 P6 4 P6 4

6 O2 19 P2 2 P13 4 P13 4

7 P56 19 P6 2 P22 3 P22 3

8 O9 18 P32 1 P12 3 P12 3

9 P58 17 P48 1 P2 3 P2 3

10 P15 15 P3 1 P33 3 P33 3

As for the received messages (in-degree centrality), the same participants appear to

have incoming messages posted specifically for them; this is more apparent in the

research pool where exactly the same e-learners were in the top 10 as there were

central students controlling in-coming and out-coming connections. In addition, the

increase of in-degree centrality indicates that they were more communicative and

received more messages; the simultaneous slight decrease in the out-degree

messages indicates that they lost some of their power and this power was distributed

to the other e-learners. In other words, the responses were originated from a group of

members that was larger than the group that received the messages. In a way, it

indicated a movement from a powerful group of e-tutors to a group that was working

more and more collaboratively to increase their learning; the active participants

became more democratic in their communication instead of maintaining their status.

Closeness: Nodes with low closeness scores have short distances from the others.

In other words, a node has high closeness centrality if it has very short

communication paths to the others. ‘In-closeness centrality’ is measured as a

function of the minimum geodesic distance from all other nodes to the selected node;

while ‘out-closeness centrality’ is measured as a function of the minimum geodesic

distance linking that node to the other nodes. While degree centrality measures use

only direct and local connectivity information, closeness centrality measures also use

indirect connectivity information (Braha & Bar-Yam, 2004:25). An example for its use

is the following (Borgatti, 2005:59): organizations with low closeness in an R&D

technology-sharing network can develop products sooner than others; a virus can

sooner infect the members with low closeness.

As with degree centrality, with regard to in- and out- closeness, there were major

differences between the e-tutors and e-learners in the two environments. This was

indicated by the closeness score, the means and standard deviation. For example,

including the e-tutors in Moodle@GSN the in-closeness score was 73.97%

(SD=10.762) and the out-closeness score 78.30% (SD=11.387); without the e-tutors

in Moodle@GSN, the in-closeness score was 32.68% (SD=1.859) and the out-

closeness score 55.04% (SD=2.532). In the research pool the results are more

equally distributed and distance of communication was reduced: with the e-tutors the

in-closeness score was 49.49% (SD=5.147) and the out-closeness score 42.74%

(SD=5.088); without the e-tutors the in-closeness score was 49.83% (SD=4.919) and

the out-closeness score 42.53% (SD=4.626).

Overall, ‘in-closeness centrality’ represents the speed of interaction from all other

nodes to the selected node; so in Moodle@GSN this speed was high when the e-

tutors were included; the standard deviation was high as well. ‘Out-closeness

centrality’ represents the speed of interaction from one node to the other nodes; this

score and standard deviation was also high in Moodle@GSN. These scores

indicated that the e-tutors were controlling the speed of information flow. However,

the scores without the e-tutors and in the research pool were more equally distributed

and the standard deviation was very low, indicating a more stable interaction speed

between the e-learners. A reason may be that e-tutors were connected more times

than the e-learners and this affected their interaction speed.

Betweennes measures the node’s prominence according to its position in the

network as an intermediary measuring the volume of traffic moving from each node

to every other node that would pass through a given node. Some active participants

act as “brokers” or “gatekeepers” between groups of nodes, therefore playing an

important role in the network. As for betweenness, e-learners stayed significantly

behind me (32.71) and the e-tutor 52 (18.7) in Moodle@GSN; P24 scored 5 and

others 2 (P32), 1.7 (P24) and 0.9 (P37). As before, this might be affected by how

long they were on-line. The scores remained on the same level in the research pool

with and without the e-tutors: 16.2 from P52, 11 and 11.8 from P18, and 6.7 and 7.3

(P24). It was evident that the highest values came from the e-tutors in Moodle@GSN

and the e-learners in the research pool. There was a significant difference between

the information gatekeepers as regulators of the information flow in the network

within the two environments despite the fact that the participants did not see any

particular roles or, to a small extent, e-tutors and e-learners. The participants with the

lowest betweenness values could be considered outsiders in the conversation, or

with no mediation power (Willging, 2005:51). These can be located in the low active

participation level; they can be classified as low active participants or, in SNA,

isolates. Lastly, there was no active participant who could control the information flow

in both environments.

Overall, the centralisation indexes were: for interaction direction (in- and out-degree

centrality) the in-degree centrality increase and the out-degree centrality decrease

indicated that the e-tutors had the power in the information flow in Moodle@GSN and

the e-learners in the research pool in a more distributed manner. This was also

evident in the interaction speed (closeness) and control (betweenness) that showed

that the e-tutors hold the network power in Moodle@GSN whereas this power was

quite evenly distributed in the research pool and the discussions have not been

monopolised. Moreover, there was no single participant who ranked high in all the

centrality measures in both environments including the e-tutors and myself.

Other than global Social Network Analysis (SNA), local SNA describes the human

and information network in a particular situation. The Visualisation Interaction Tools

Nodes and Centrality (VIT Nodes and VIT Centrality) supported local SNA nodes and

centrality in real time.

6.5.7.3. Local Nodes and Centrality in Real-Time

Just as a photo and a recording give a different ‘picture’ of two people

discussing something, so too, two SNA tools running in real time aimed to provide a

different viewpoint of the discussion and triangulate the events of active participation

and collaborative e-learning. Visualisation Interactions Nodes (VIT Nodes, Figure

6.5.7.3-1) and Centrality (VIT Centrality, Figure 6.5.7.3-2) were integrated in Moodle

in the research pool. A different abstract representation was given with regard to

interaction density (weight), reciprocity (preferences) as well as in- and out-degree

centrality (direction). Closeness as the interaction speed was represented on both

graphs as the geodesic distances indicate the temporal distance between the

messages. Information control (betweenness) could also be observed. (Note that the

participants were not given specific information on the exact use of these tools as the

tools should indicate their own use (usability).)

In VIT Nodes the individuals are represented as circles (nodes), the direction of the

messages is indicated by an arrow and the number represents the number of

messages (Graph 6.5.7.3-1):

Graph 6.5.7.3-1: VIT Nodes in CeLE IX

P37 was the information broker in this CeLE. The reciprocal tie with O2 was an

argument. She also responded to her own message a couple of hours later after the

argument with O2. Most participants were replying to P37 and two of them talked to

each other. It is interesting that this CeLE was developed by different individuals with

only two interlocutors exchanging 2 messages. In other words, the discussion was a

collaborative activity between 7 individuals. VIT Centrality provided a different

viewpoint (Graph 6.5.7.3-2):

Graph 6.5.7.3-2. VIT Centrality in CeLE IX

In VIT centrality P37 is clearly located in the middle of the e-learning social network.

VIT centrality also indicates the response time space related to geodesic distances

between the participants. As a central connector and information broker she moved

the knowledge around leading to a new proposition by taking into account her co-

learners responses even though they appeared as low activity e-learners (i.e. only

O2 was an e-tutor).

Overall, the Visualisation Interaction Tools Nodes and Centrality provided

opportunities to the e-learning participants to observe their personal styles and

performance within the e-learning community as well as observe small groups

created within their discussions. Being self-aware corresponds to self-organised

learning and development. Information organisation roles can be unofficially assigned

to e-tutors to support the collaborative e-learning development.

To sum up, it appears that after the initial knowledge acquisition and information

exchange, the collaborative techniques and tools helped participants to learn from

the e-tutors, their co-learners and on their own. As they did not have any previous

knowledge of collaborative learning and techniques they acquired this knowledge for

community knowledge building. This means that e-tutors have a complex job that

incorporates moderating as well as e-tutoring (Salmon, 2000). It was also suggested

that knowledge awareness plays a major part in the creation of opportunities for

efficient and effective collaborative opportunities (Ogata & Yano, 2000) which leads

to the fact that different learning styles are supplementary to each other in e-learning

environments.

Lastly, with regard to collaborative e-learning quality, the participants learned from

the e-tutors (instructional learning), the other e-learners (collaborative learning) as

well as on their own how to work together and how to use the new tools and new

technologies (vicarious and self-organised learning). Almost the same number of

collaborative e-learning episodes, 6 in Moodle@GSN and 7 in the research pool, add

to the evidence for the e-learning quality. CeLE was found to build on progressive

discourse and fill the middle space between internalisation and externalisation in the

form of monological to dialogical sequences. This was evident not only within one

CeLE but in the participation process as monological postings stand alone without

open clues for dialogue as in information provision. In a way, e-learners were

progressively adopting a two-way communication. This means that there were more

clues as opportunities for critical engagement in dialogue in the research pool caused

by two events, the initial need for familiarisation with collaborative e-learning in the

early stages of the online course and the sleeper effect, and the use of MessageTag

that revealed the collaborative e-learning structure. Moreover, correcting

communication gaps between the collaborative learning discussion stages is feasible

for the e-learning participants.

The effectiveness of the Sense of e-Learning Community Index will be discussed in

the interventions section at the end of this chapter.

6.6 PEDAGOGICAL USABILITY

The participants’ responses in the closed question revealed that the new tools

supported the e-learning community development (n=33, 82.5%). The tools were: (a)

Participation graphs and avatars; (b) MessageTag; (c) Visualisation Interaction Tool for

Nodes (VIT Nodes), and (d) Visualisation Interaction Tool for Centrality (VIT Centrality).

The overall results are presented in Appendix XII.

6.6.1 Pedagogical Usability

The participants responded to 15 closed questions on a Likert scale 1-5. In

sum, the pedagogical usability values were (Table 6.6.1-1):

Table 6.6.1-1. Pedagogical usability values

PEDAGOGICAL USABILITY VALUES

1 Instructions 3.6 2 Frequency of use 2.4 3 Alignment with educational goals 3.5 4 Support collaborative e-learning 3.5 5 Learnability 2.7 6 Accessibility 3.7 7 Originality 3.4 8 Motivation to participate 3.5 9 Information overload 2.8 (5.0-2.2) 10 Tool failure 3.1 (5.0-1.9) 11 Functionality 3.4 12 Graphics 3.4 13 Attractiveness 3.0 14 Fast response 3.6 15 Overall satisfaction 3.4

Overall 3.2 Values 9 & 10 were inverted for reasons of compatibility and clarity

The overall score for pedagogical usability was found to be just higher than the

average of 1 to 5 Likert scale (3.2). Most of the pedagogical usability scores for the

new collaborative tools were satisfactory. However, originality (2.4) and learnability

were low (2.7). The law learnability rating may explain why the tools were

infrequently used (2.4). This result was similar to the preliminary studies although

there the tools were being used by the developers who perceived the tools

differently. Nonetheless, according to the participants, the use of the new tools was

the third best thing in the project after collaboration and feeling a sense of

contributing to something great (Appendix A_XII_4).

The messages were tagged with MessageTag (Table 6.6.1-2):

Table 6.6.1-2. Use of MessageTag in the Research pool

USE OF MESSAGETAG IN THE RESEARCH POOL Forums CeLE Attributes # use Tagged messages Percentage

Inform 0Question 0Explain 0Explore 0Agree 0Evaluate 0Summarise 0

Other 0

Inform 7Question 3Explain 3Explore 2Agree 2Evaluate 2Summarise 0

VC in E-learning

Other 1

20/70 28.6

Total 20/79 25.3

The tool was not used in the introductory news section and the participants started

using it in the main discussion. The results were very similar to the e-mmersion

block; 20 out of 79 messages were tagged with an average 27.3% use. Comparing

the results with the developers’ results (55.3%) a great difference appears to be

between the way average users’ utilisation of the new tools and the more advanced

users. Involving users with different levels of experience or filtering of users based on

their profile for basic and advanced user testing can provide different results;

advanced users might know uncommon ways to overcome problems on the

interface, get familiarised quickly or be keen to experiment with new tools.

Interestingly, P6 sent a message to the forum saying that the new tools are invisible

and lost in the interface. He said that most users will not notice them and he gave

examples on MessageTag and Visualization Interactions Tools nodes and centrality:

“it is not easy to actually see the links that lead to them because the MessageTag is

at the end of the message and the images for the VIT are invisible”. In addition, his

message indicated frustration concerning their use which is in accordance to the low

learnability score: “At last! I managed to find a way with the VIT nodes and

centrality…” (“Επιτέλους! Έβγαλα μια άκρη με τα VIT nodes & centrality.”). Lastly, he

expressed his enthusiasm about the tools and suggested that their use will be

determined by time.

P6’s messages raises questions on the decisions made about the images selected

after the developers’ recommendations. A developer needs to listen to users’

opinions; however, her decision making is based on her own expertise and usability

tests in usability laboratories, especially when the developers’ sample is relatively

small. (There were 3 Greek teachers who were Moodle developers participating in

tools’ testing.) It also appears that new tools need more than one week of use and

evaluation. However, the use of visualisation interactions tools was not apparent

without the aid of the literature; this is in contradiction to usability rules as the tools

should be easy to use. As tools to represent social networks have now reached the

average user (e.g. different social network applications on Facebook,

http://www.facebook.com), their utilisation will be more obvious and the users will be

more familiar with their practicality.

Overall, in comparison to the previous usability evaluation in the two preliminary

studies with e-learners and developers, the actual e-learners scored significantly

less; for example, all previous scores were much higher than the average (>4), and

no differences appeared between the participation and collaborative e-learning tools,

and VIT. This also means that the ‘real’ users are more reluctant to use the tools.

The participation graphs and avatars as well as the MessageTag achieved more

scores than the Visualisation Interactions Tools (VIT) in all pedagogical usability

metrics. The alignment with the educational goals and support for collaborative e-

learning was more than the average. In other words, the relevance of the tool to the

particular task had a positive effect. From an HCI viewpoint, as Draper (1993)

suggested, this was the relationship between the task and the method. He also said

that usability measurement of one task cannot be applied in exactly the same way for

all users. In addition, because the design process is technical and social, new

products development requires cycles of communication between the organisational

stakeholders (Safayeni, et al., 2008).

This section discussed results from the questionnaires, the tools, and the

participants’ comments. The next section refers to the most noticeable correlations

and crosstabulations between the pedagogical usability and utility factors as

appeared in the questionnaires.

6.6.2 Correlations & Crosstabulations

Two ways were found suitable to measure and analyse inter-correlations

between the participants’ responses in the final questionnaire, in SPSS (Appendix

A_XII_1-2) and in Hierarchical Clustering Explorer (HCE) (Appendix A_XII_3). SPSS

was used to find all correlations as well as the ones related to specific issues. HCE

provided an overview of correlations focused on the most important positive and

negative correlations.

In more detail, the matrix with the data was exported from SPSS to Excel and then

inserted in the HCE to distil them. In HCE, N/A were viewed as missing data, and all

data were initially filtered with SD≤1. Twenty out of 40 rows remained and then, in

order to increase similarities and reduce differences between the data, the data were

normalized row by row in a scale 0.0 to 1 using the equation . Then Pearson’s r

correlation coefficient was used to identify 1,770 correlations variables with lower

score -0.747 and highest score 0.981 (scores<1). The information visualisation

provided a simultaneous correlations overview, scatter plotting, and in depth analysis

(Figure 6.6.2-1):

Figure 6.6.2-1. Correlations analysis in HCE 3.0

HCE provided a correlations overview from the questionnaires (bottom left), scatter

plotting (bottom right), and in-depth analysis of the results. The latter means that

clicking on the participants (top left) located them on the scatter plot; additionally

there was a visual summary (top right).

Not all 1,770 variables are presented here; the variables with r>0.7 (0.977<r>0.703)

and r>-0.600 (-0.600>r<-0.747). As in the previous findings, it appeared that

correlations exist between the two groups of tools the collaborative e-learning and

participation tools (Participation graphs and avatars, and MessageTag) as well as the

Visualisation Interactions Tools Nodes and Centrality (VIT Nodes, VIT Centrality)

used for social network analysis. This can be explained under the rubric of

functionality; the two groups of tools supported different practices in discussions, the

first to structure and analyse collaborative e-learning, and the latter to support

visibility in social networks. In other words, the practicality of the first was more

explicit than the latter.

The positive correlations between participation graphs and avatars, and MessageTag

were: failure (r=0.944); accessibility (r=0.948); educational goals (r=0.883); fast

response (r=0.751); motivation to participate (r=0.71); educational goals and

functionality in graphs and avatars alone (r=0.782); and satisfaction and educational

goals in graphs and avatars alone (r=0.712). The results show that there were

problems concerning tools failure and accessibility; however, there were in

accordance to educational goals, motivated participation, and the e-learners

expressed their satisfaction. This preference was also evident in the average use

(Likert scale 1-5): for graphs and avatars 2.7 (SD.=1.3); and for MessageTag 2.7

(SD=1.2).

The positive correlations between the VIT were: where Nodes failed, Centrality failed

(r=0.977); where Nodes functioned, Centrality functioned (r=0.961); satisfaction

(r=0.955) and motivation to participate was related (r=0.930). Originality was found to

be an issue only for VIT Nodes, related to: educational goals (r=0.81); functionality

(r=0.771); graphics (r=0.752); satisfaction (r=0.721); and support Collaborative e-

Learning (CeL) (r=0.712). In Nodes alone functionality was also found relevant to

satisfaction (r=0.792); motivation to participate and support CeL (r=0.788);

satisfaction and support CeL (r=0.748); and satisfaction and graphics in visual design

(r=0.710). In Centrality alone correlations were found between: satisfaction and

functionality (r=0.801); satisfaction and support CeL (r=0.784); satisfaction and

graphics in visual design (r=0.777); accessibility and instructions (r=0.763);

functionality and graphics (r=0.729); functionality and attractiveness (r=0.722); and

graphics and attractiveness in visual design (r=0.718). More meaningful correlations

between Nodes and Centrality were on: instructions (r=0.961); and graphics and

attractiveness (r=0.718).

Less strong negative correlations appear only for the VIT. For VIT Nodes the results

were: satisfaction was negatively related to failure (r=-0.0609); motivation to

information overload (r=-0.632); information overload and attractiveness (r=-0.6776);

learnability and attractiveness (r=-0.712); and accessibility and learnability (r=-0.729).

For VIT Centrality the results were: information overload and motivation for Centrality

(-0.628); satisfaction and information overload (r=-0.629); information overload and

attractiveness (r=-0.747). It appears that information overload was the main and

learnability the second pedagogical usability problem that affected attractiveness,

motivation to participate and the overall satisfaction. VIT were not used as much as

graphs, avatars and MessageTag: VIT (Likert scale 1-5): VIT Nodes 2.1 (SD=1) and

VIT centrality 2 (SD=1).

The difference in the standard deviation on the use of tools showed that some e-

learners used the tools more frequently than others. After crosstabulating the first

and final questionnaires, it seemed that the e-learners who did not have any

experience of LMS used the new tools more than the experienced e-learners (Table

6.6.2-1):

Table 6.6.2-1. Time using LMS * Frequency of Use

CROSSTABULATIONS: TIME USING LMS & THE FREQUENCY OF USE

Graphs/avatars MessageTag VIT Nodes

VIT Centrality

Time Using LMS

# # # # Mean

1 1-3 2 2 2 2 22 4-6 1 1 1 1 1

Missing 3 3 3 3 33 Months

Total 40 40 40 40 404 0 22 22 22 22 225 1-5 13 13 13 13 136 6-10 1 1 1 1 1

Missing 3 3 3 3 37

N/A 1 1 1 1 1Total 40 40 40 40 40

The participants gave similar results in regard to the tools. Similarly, the e-learners

who did not have any training on LMS used the new tools more than the trained e-

learners (Table 6.6.2-2):

Table 6.6.2-2. Training on LMS * Frequency of Use

CROSSTABULATIONS: TRAINING ON LMS & THE FREQUENCY OF USE

Tools Graphs avatars MessageTag VIT

Nodes VIT

Centrality

Train LMS

# χ2 # χ2 # χ2 # χ2 1 Yes 11 11 11 11 2 No 26

3 Other 1 1 1 1 4 Missing 2 2 2 2

Total 40 40 40 40

As before, the responses are similar; the participants with no training at all used the

tools more than the others, less the ones attended an ICT course and even less the

ones who had proper training within universities. This may mean that the more

experienced the e-learners the more reluctant they are in the use of new tools.

Another explanation may be that the users who were familiar with Moodle hardly

noticed the new tools in the research pool and acted by habit.

Pearson’s correlations were also calculated for the two tables. The variables were

checked for being ordinal or categorical, no cell to have expected values less than

one, and no more than 20% of the cells have expected values less than five (Muij,

2003). In addition, because in the two rows and two columns (two-by-two tables)

case of the second table, chi-square becomes unreliable, Yates’ correction of

continuity was performed instead. Although there are arguments in the research

community against its use (e.g. Haviland, 2007), Yates’ correction of continuity is

automatically calculated in SPSS statistical output to prevent overestimation of

statistical significance for small data.

Overall, it appears that the graphs and avatars as well as MessageTag received

higher scores than VIT Nodes and Centrality. It seems that the first were found more

practical and relevant to the specific practice. In particular, the visibility of active

participation levels structure in the graphs and avatars may have helped e-learners’

reflection on their participation. Their effectiveness is a device for information

retrieval as the visual objects (graphs and avatars) provide users with the elements

to explore and reflect. E-learning tools need to address such participation trajectories

(Suthers, 2006). Accordingly, the visibility of the collaborative learning structure in

MessageTag seemed to help e-learners’ reflection and increased challenges per

argument. However, if compared to the results in the previous studies, for

participants lacking certain skills, training and experience in association to using new

tools may have been a disadvantage. Nonetheless, opening interaction spaces in

participation, collaborative e-learning, and social networks seemed to be essential.

6.7 INTERVENTION ANALYSIS

The intervention analysis can be depicted as follows (Table 6.7-1):

Table 6.7-1. Intervention Analysis

Target Intervention Analysis

A. Form of the effect Level Adequate Slope √ Variance - Cyclicity Adequate B. Permanence Continuous √ Discontinuous - C. Immediacy Immediate √

Participation in the Greek teachers’ collaborative e-learning community

Delayed -

The target in this study was to investigate participation in the Greek teachers’ e-

learning community and provide tools and evaluation techniques to support their

development. In the intervention analysis the form of the effect, as in level, slope, and

cyclicity, was successful. The treatment was immediate and its permanence was

continuous to this point in time. More specifically the overall discussion on the

suggested tools and evaluation techniques is as follows:

E-learning engineering was found to require five corresponding changes:

• a fundamental change in perspective;

• a commitment to situated approaches;

• the coherence of action as an emergent property of moment-by-moment

interactions between the actors and between the actors and their

environment;

• unification of design, evaluation, and use under the rubric of community

and real-time research; and

• building interventions in ‘time-boxes’ to achieve coherency of action.

Thus, the suggested model for e-learning engineering is (Table 6.7-2):

Table 6.7-2. E-learning engineering

E-LEARNING ENGINEERING Design Stages Ethnotechnology

A INTENT 1. Prerequisites: real need & right

attitude 2. Goals: stakeholders’ goals,

requirements & variances Scenic fieldwork

Ethnographic inputs

B PLANNING

3. Documentary review 4. Background studies: description of

stakeholders background & characteristics

5. Interdisciplinary research • Evaluation for the targeted

pedagogical approach (intentional variance)

• Evaluation for the targeted technical problem (operational variance)

• Pedagogical Usability guidelines

C ITERATIVE DESIGN

6. Design for initial design • Apply guidelines from

feedback for design 7. Create one prototype for user-learner

testing • Evaluation to acquire

feedback for redesign 8. Redesign and evaluate with user-

learner to redesign

Implications for design

D EVALUATION & USE

9. Implementation in situ 10. Evaluation & feedback

Scenic fieldwork

R E A L - T I

E V A L U A T I O N

Initially, design was used as a problem solving activity in which the problem was broken

down into a number of sub-problems, solved independently and reintegrated to produce

a design solution. In order to do this, the value of unarticulated expertise and tacit

knowledge was acknowledged. Design was found to be a reflective process having a

post hoc nature (Suchman, 1987) and evolved over time integrating design, use and

evaluation (Bannon, 1994). Such approaches have been found in the history of

engineering design as nowadays design requires flexibility between various ways of

thinking (McGarry, 2005).

Collaborative e-Learning Episodes found to be a successful analytical framework

in regards to e-learners’ use as well as in their in-depth analysis. This structure

allowed e-learners to externalise their thoughts in order to reflect upon them. Their

attributes, initiation, explanation, exploration, evaluation, co-construction, were

visualised in MessageTag as Inform, Question, Explain, Explore, Agree, Evaluate,

Summarise, and Other. Translating a theoretical framework into a tool was found

difficult and it was not easy to create a tool that could be used without instructions.

However, iterative design made the tool more accessible to the e-learners and it

became the most successful tool in this study.

Active and passive participation levels in collaborative e-learning were found to be

related to social interactions and thus grouping as the participants’ interactions were

more and more intimate. The interactions depended on the learning styles and the

personal learning goals as active and passive participation were found to have an

idiosyncratic character. E-learners’ interpersonal and intrapersonal skills were found

to control the dynamics of the collaborative e-learning networks. In other words,

learning emerges from passive and active participation in collaborative e-learning

suggesting intentional rather than reactive behaviour. The tools based on the

participation were successful; graphs and avatars were found to be in accordance to

their purpose, however, missing their log files because of their failure without having

time to repair them prevented triangulation from the results.

Visualisation Interactions Tools were VIT Nodes and VIT Centrality. They depicted

the local networks in a particular discussion and were found to be less important for

collaborative e-learning. As they were built on SNA, the participants were unfamiliar

with them and it was difficult to interpret their use and incorporate it in their practice.

Another explanation may be the absence of a direct match between the task and the

method (Draper, 1993); this means that SNA methods were not explicitly connected

to the Greek teachers’ educational practices and thus, their working methods.

The Moodle discussion application was found to be rigid; in fact some participants

complained about the simplicity of the forum when they got back to Moodle@GSN.

The tools aimed at reducing misleading information and interruptions by triangulating

the otherwise separated information context and e-learners’ network; representation

of the progressive dialogue and relationships between the messages can provide a

more coherent view of the research context. This also means that e-learning

participants can manipulate information, knowledge, and interactions as interrelated

areas of one situated context in order to achieve their goals.

The Sense of e-Learning Community Index (SeLCI) provided a different viewpoint

to describe the e-learning community and processes in depth (only the e-learners’

results were considered in social network analysis) (Table 6.7-3):

Table 6.7-3. The Sense of e-Learning Community Index Checklist

THE SENSE OF E-LEARNING COMMUNITY INDEX

Attributes Moodle@GSN Research Pool

1 Community evolution √ 2 Sense of belonging √

Intensity Levels of participation Interrupted Coherent 3 Persistence 80% 95.3%

4 Empathy √ Social Network Analysis

Group Cohesion Density 0.0256 0.0418

Reciprocity – reciprocal ties 0.2222 – 4(28%) 0.2174 – 10(71.4%)

Cliques 4/3 actors 12/3 actors 1/4 actors

Structural equivalence - 3 second level groups - 4 participants with identical behaviour

- 5 1st level groups - 2 2nd level groups 1 solo-actor positions.

Group Centrality In-Degree 5.425% 6.671% Out-Degree 10.826% 9.372% In-closeness 32.68% 49.83% Out-closeness 55.04% 42.53%

Betweenness 2(P32)

1.7 (P24) 0.9(P37)

16.2 (P50) 11.8 (P18) 7.3 (P24)

6 Trust √ Collaborative e-learning quality

Participants’ opinions √ 7 Number of collaborative e-learning episodes. 6 7

Time 31 days 6 days

Overall √

SeLCI was found to be successful in describing, evaluating and triangulating the

research context. Sharing their interests and values, the participants responded in a

positive manner about community evolution, sense of belonging, empathy and trust.

Intensity was above the average level and more coherent in the research pool.

Establishing sociability and common ground was the first level towards a progressive

course in collaborative e-learning.

It is also interesting to note that the sense of community was evident in the participants’

communication outside the course. For example, the e-tutors other than myself met for

the first time in a conference in Athens (7 October 2007). When I asked them via

electronic communication whether they could describe the feeling they had they said that

it was like being old schoolmates. In addition, the respondents’ comments in Other on

the final questionnaire were in accordance to the checklist. For example, P14 said he

was looking forward to login; familiarisation with the other participants and the interface

was immediate even though it was the first time he was participating in an online course.

He didn’t expect to have the same strange feeling when something like a live conference

is over. There was an interesting observation from P35 about activities and

communication: “Many people were collaborating at the same time I saw that I can

change things with my participation both as a student and as a facilitator. The formal

educational authorities do not actually know what this is about; it is a programme in

parallel with the official one (παρα-πρόγραμμα). Hope new technologies will change

things”. The participants experienced innovative collaborative e-learning tools and

techniques and stressed the importance of incorporating them in the Greek teachers’

training cycles.

Comparison with recent studies: In the recent research, Daniel in his PhD Thesis

(2007), tested 11 dimensions to sense of community within 15 undergraduate students

using an e-learning environment. There were differences in the number, age, profession

and experience of the participants; additionally, as he used a questionnaire and message

analysis to obtain his results there were several differences and similarities (p.111-126).

For example, he measured reciprocity by assessing participants’ frequency of sharing

class related resources; he related trust to the levels of awareness and co-presence. He

also measured learning as knowledge awareness depending on information about other

e-learners’ activities, that was what individual knew (competence awareness) and what

they could do (capability awareness) (p.126-127). (Note that Daniel did not always

describe his findings using numeric representation.) The similarities were:

• Participants continued their networking outside and beyond the time frame of

the class (p.111).

• The feeling of belonging to the community was high (p.113).

• There was a high ratio of shared goals and values (p.116).

• On participation and social protocols 67% of the participants said they were

aware of them.

• Peer support was evident and reinforced members’ sense of belonging

(p.120).

• There were high rates of social networking.

• Most participants did not know each other before the course (56% said they

knew nobody, p.124-125).

• E-learners’ knowledge awareness bred trust to the community. And

• People discovered they had similar problems and interests.

In another study on online social identity, knowledge construction and passive

participation for nurses participating in an online course, Gulati (2006) found that there

were different forms of learning and different types of e-learners depending on how

sociable they were. (Note that there are no page numbers as the thesis was not on a

PDF format and there were differences on the page numbers in the chapters.) Her

investigation was mainly qualitative and the similarities to this study were:

• The participants enjoyed learning together.

• They felt part of the group.

• They exhibited desire to be connected.

• They shared same interests and responsibilities.

• Online communication skills were crucial to enable participation.

• Time was limited.

• There were access problems.

To finalise, none of the participants knew the specific aims and objectives of this

project when they replied on the open question about the best things they

experienced in the course; these were: their participation in collaborative activities

(11 responses); feeling of belonging to something greater (7 responses); having

common interests and targets (6 responses); and the use of new technologies (9

responses). (For all results see A_XII_4). P2 said that she needs ‘to look for people

more, since there are others who look for the same thing and can be useful’. (Να

ερευνώ από δω και πέρα περισσότερο γιατι υπάρχουν τελικά και άλλοι που ψάχνουν

το ίδιο και μπορούν να φανούν χρήσιμοι πάντα.). P47 expressed her ‘satisfaction that

there are many colleagues interested in the further development of educational

practices’. (...ικανοποίηση ότι υπάρχουν αρκετοι συνάδελφοι που ενδιαφέρονται για

την βελτίωση εκπαιδευτικών πρακτικών.) P45 said that ‘the still waters start to move

in the area’. (...Πιστεύω ότι σιγά - σιγά αρχίζουν να κινούνται τα λιμνάζοντα ύδατα

στο χώρο.)

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Tools & Evaluation Techniques for Collaborative E-Learning Communities Chapter 7: Conclusions

Conclusions: Summary of the thesis, contributions and recommendations

Key Topics covered in this chapter:

• How the thesis reached this point

• Exploring the contributions to existing knowledge

• How this study is limited to this particular context in time and e-learning space

• Recommendations to the participants in the e-learning design

• Suggestions for future directions

• The conclusion derived from this study

Chapter 7 provides a summary of the thesis and explores its contributions to

knowledge. In addition, it presents the main blocking factors for the Greek teachers’

passive participation, the implications from the findings, the limitations, the

conclusions as well as some future research directions.

7.1 INTRODUCTION

The aim of this chapter is to examine the scope of the findings, to put them into

the context, scrutinize the strengths and limitations of the work and suggest

implications for findings and directions for the future investigations might take.

7.2 SCOPE OF FINDINGS

In this section the scope of the research and the overall findings are described

in relation to the aim and objectives. This study aimed to carry out the following with

regard to Collaborative e-Learning Communities:

Thus, this study set out to answer a number of exploratory questions; the conclusions

are presented next.

Collaborative learning research is multi-disciplinary. Cognition is a complex social

phenomenon based on the individual’s re-arrangements of knowledge influenced by

social interactions. Social interactions provide the common ground for discussion that

occurs on two levels: internalisation of knowledge as reflection from passive

participation, and externalisation of knowledge as active learning from active

participation. These two levels are found to be brought together in collaborative

learning as a socially shared cognition problem solving and evaluation technique.

This process was reflected in the literature review in a progressive way, from the

study of the individual to the study of groups and communities. This exact process is

also reflected in the structure of the current educational systems that fail to follow the

last step towards community knowledge building and thus, resulting in the e-learning

passive mode. In other words, available learning management systems do not

support users’ in co-creating the e-learners-generated context.

There have not been many attempts to support collaborative e-learning from a

community viewpoint; finding suitable variables to describe and support increasing

participation was part of the problem. Additionally, design was found to be

inadequate to carry the social interactions; it is legitimate for the participant to be in

any participation level. As a result, all Greek teachers never crossed the threshold of

passive participation for 3 years because of personal, social, learning, institutional or

technical obstacles. In other words, if the e-learners were adequately supported by

tools and evaluation techniques then passive participation would drop to the

minimum.

No coherent frameworks were found to support increasing participation in

collaborative e-learning communities.

For the past 50 years two main trends have been observed in education, the socio-

cultural focus and the use of technology. However, these two trends have evolved

almost separately. Socio-technical design and user-centred design were planning

approaches aiming to acknowledge that the development of interactive technologies

increasingly relies on an appreciation of the social circumstances in which systems

are used. Design is planning; educational or instructional design is the systematic

processing of activities to solve an instructional problem with the aid of technologies.

However, educational design and in particular e-learning design neglected the dual

and situated persona of the learner; she acts as both a user and a learner. In

addition, the e-learning systems were found to be information-based mainly

supporting monologue instead of being communication-based towards dialogue. For

this reason they fail to support e-learners’ transition between internalisation to

externalisation and becoming active participants. Thus, mere provision of information

points to poor e-learning quality. So, if educational design could understand the

technology of collaborative practice, e-learning quality could be improved.

The first signpost was the radical view that design is planning with a post hoc nature.

This means that situated design needs to follow the evolution of its context, in this

case, the collaborative e-learning community. The second signpost was the

development of a social and technical infrastructure that supports the key activity, in

this study, collaborative e-learning. The third signpost was the real-time setting of the

key activity and its evaluation. The last signpost was the involvement of e-learning

participants in the design. These guidelines suggested ethnotechnology as the

methodology to inform design on a social, learning, and technical level.

No tools and techniques were found to evaluate the process of increasing

participation in collaborative e-learning communities as progressive discourse.

Several projects investigated the use of progressive dialogue to support collaborative

leaning. However, none of the projects targeted to the creation and development of

an active collaborative e-learning community.

Therefore the answers to the exploratory questions led to thesis contributions.

7.3 CONTRIBUTIONS

The second set of questions suggested specific schemes to tackle passive

participation and poor e-learning quality. These were the key contributions of the

thesis. Nevertheless, there were also secondary contributions.

7.3.1 Key Contributions

The Collaborative e-Learning Episode (CeLE) was proposed as a coherent

and cyclical analytical framework to identify, analyse, and evaluate contributions in

Collaborative e-Learning Communities (CeLC). The main attributes were found to be:

inform, question, explain, explore, agree, evaluate, summarise, and other. The CeLE

was found to support Greek teachers’ progressive discourse, reflection, critical

thinking, and co-creativity.

The Sense of e-Learning Community Index (SeLCI) was developed and

successfully tested based on collaborative e-learning community sociodynamics and

collaborative e-learning. SeLCI consists of indicators to understand how a community

functions as well as being determinants for its success. These were: community

evolution; sense of belonging; empathy; trust; intensity characterised by e-learners’

levels of participation and persistence on posting; collaborative e-learning quality

measured by the number of CeLEs and participants’ comments on their learning; and

social network analysis based on: global cohesion anchored in density, reciprocity,

cliques and structural equivalence, global centrality derived from in- and out-degree

centrality and closeness; and local nodes and centrality in real time. These

determinants were analysed on a temporal basis towards the evolution of the

collaborative e-learning community.

In addition, a coherent and measurable framework was developed upon the

increasing participation process: zero, low, medium, and high passive participation,

and low, medium, and high active participation. Lastly, the transition between passive

and active participation was called the sleeper effect.

The post hoc structure for E-Learning Engineering was revealed integrating design,

evaluation, and use, this involves all e-learning participants in design, and is informed

by ethnotechnology and real-time evaluation tools.

Quality by design in e-learning appeared to be related to a complex web of factors.

Some of these factors have been investigated and determined in each of the

previous exploratory questions. A conscious effort to tackle some of them was based

on the suggested tools and evaluation techniques found to have solved the initial

problem of passive participation and e-leaning quality.

The participation graphs and avatars that depicted active participation were found

to have supported increasing participation in collaborative e-learning. This was due to

the fact that they were built on the technology of participants’ real practice.

MessageTag was the tool built on the CeLE analytical framework. As with the

participation tools, it successfully supported e-learners because of its relevance to

the key activity, that was collaborative e-learning.

The Visualisation Interactions Tools Nodes and Centrality were found to be less

supportive in the e-learner’s endeavour and had the most problems from a

pedagogical usability viewpoint. However, it appears that their use aided the

participation of the Greek teachers in their e-learning community.

7.3.2 Secondary Contributions

The secondary contributions refer to e-research methods and pedagogical usability.

1. Ethnotechnology was the exploitation of ethnography in design aiming at

better understanding of the context under investigation. Although it is

unadvisable for Ethnotechnology to be conducted by one person being

ethnographer, designer, e-tutor and researcher it was unavoidable in this

study. The use of ethnotechnology provided insights by:

a. Facilitating investigation on relations within a situated context for

i. The collaboration and interaction between the Greek

teachers

ii. The role of external factors such as lack of legislation and

slow Internet connections

iii. The management of human-human interactions

b. Facilitating investigation on human-computer interaction for

i. The use of tools by users as learners

ii. The use of tools by learners as users

c. Supporting feedback for design on

i. The translation of tasks into tools

ii. The emergence of alternative options and perspectives

d. Increasing understanding for tasks and associated practices for

i. Investigating e-learning participants’ roles, needs, targets,

and visions

ii. Transferring of knowledge within the organisation

iii. Rising levels of expectations and enthusiasm

iv. Supporting community’s continuity and Greek researchers’

professional learning

v. Advancing best practices in researcher’s own community

2. Triangulating qualitative and quantitative data with social network analysis

increased:

a. The validity and reliability in the study

b. The context for diversity of perspectives

c. The emergence of alternative perspectives

d. The derivation of new concepts

3. The measurement of pedagogical usability of new tools as related to:

a. The dual persona of the learner as a learner and a user

b. The design for new tools

c. The evaluation by distinct groups of users, teachers, and

developers

d. The researcher’s self-reflection

These contributions need to be considered within the limitations that follow.

7.4 THESIS LIMITATIONS

There were several research constraints: the nature of e-research; the

circumstances under this study was carried out including time frame and

unwillingness of the Greek educational authorities to cooperate; the sample was not

representative but rather based on participants’ special interest in Information and

Communications Technology in education; and limited research in collaborative e-

learning communities. In addition, the Hawthorn effect was evident; one participant

explicitly said that she wanted to contribute to this project.

From a design viewpoint, the tools were not implemented in the real e-learning

environment for the Greek teachers future use. In addition, I had too many roles and

limited programming skills resulting in not being able to tackle a problem on the log

files for three of the tools, on time. Also, there was no usability testing of the tools in a

usability laboratory.

Lastly, the suggested tools and evaluation techniques need to be further tested and

developed in different contexts to ensure their validity and reliability.

7.5 CONCLUSIONS

This final section presents the overall blocking factors responsible for the

Greek teachers’ passive participation, the implications from the findings, and future

research directions.

The problem of e-learning quality was found to be related to the Greek teachers’

passive participation. A network of institutional, instructional, technical, and personal

obstacles acted as blocking factors on a micro and macro level:

• Diversity on the concept of e-learning quality in current research

• Traditional low value of collaborative e-learning reflected on lack of

soft skills and training in online collaboration

• Lack of national policies and coordinated activities on behalf of

educational authorities

• Lack of a variety of e-learning evaluation tools and techniques

• E-learning in Greece is still an unofficial practice based on isolated

initiatives

• Lack of time for the Greek teachers to be engaged in life-long learning

• Lack of technical support

• Lack of perceiving the direction in education in the 21st century.

In fact, these blocking factors have been reported on a European level in the recent

E-quality report (Fernandes & Montalvo, 2006) and were also identified in my

participant observation in 2 European e-learning projects. Thus, the problem of e-

learning quality in the Greek School Network was not different or more intensive than

in other European countries. This also means that although this study was designed

to be strictly situated, the recommendations for researchers, e-learning engineers, e-

learning practitioners, and the Greek educational authorities may have an impact on

e-learning quality on a broader level (see recommendations in Appendix XIII).

Implications from the findings

The findings in this study demonstrate the significance of social, learning, and

technical aspects of e-learning. Two interventions were made, collaborative e-

learning and the introduction of new tools; the first was related to community

management and collaborative e-learning, the tools were built to facilitate them. The

conceptual frameworks of the participation levels, the Sense of e-Learning

Community Index (SeLCI), the Collaborative e-Learning Episode (CeLE) analytical

framework, and the associated tools aimed to bridge the social and learning gap.

Brief description of the findings, their implications and recent related studies will be

discussed next.

Within the context of the study, the participants’ prior knowledge and ability to interact

was enhanced (Yang, 2002); there was also lack of governmental planning for e-

learning pedagogy, technology, and legislation. The implications from the first finding

suggest the need for training the Greek teachers in current pedagogical collaborative

approaches and new technologies; improvement of soft skills and communication

techniques; development of shared vision and goals; access to professional help and

support. These implications point to the problem of e-readiness for e-learning (e.g.

Kaminsky & Currie, 2008). The failure for e-readiness is evident in the great

discrepancy between different ranks in Greece (The Economist Intelligence Unit &

IMB Corporation, 2003:16); on a scale from 1 to 10, 8.80 was the government rank,

5.87 the industry rank, and 5.66 the society rank. Thus, the implications is that

organisations and business need to understand and correctly judge real situations,

trace solutions as processes, and educate and support everyone involved in e-

learning.

From a community management viewpoint, time and activities management was

anchored in the passive and active participation levels, as well as the “sleeper effect”,

the gap between the previous two levels. Increasing participation from passive to

active fostered interaction flow and continuity and thus, these levels confirmed the

concept of learning as participation (Lave & Wenger, 1991; Kanes & Lerman, 2008).

An implication is that in such favourable circumstances, passive participants are

highly likely to get engaged. These implications stress the impact of e-learners’

control in their own process of engagement as learners are usually not

knowledgeable enough to make effective decisions (Dron, 2007).

Community development was built on shared background, experiences, goals, and

visions. This was to enhance interactivity, as a key component in assessing the

effectiveness of e-learning (e.g. Zhao et al., 2005; Thurmond, 2003). Implications

from this study suggest that interactivity has to be increased prior to e-learning

activities and facilitated by reciprocity, empathy and trust. Sharing personal

information and experiences through the profiles and developing a sense of

identification and co-presence between the e-learners can foster community building.

Observing other e-learners’ behaviour and develop reciprocity empathy and trust are

interpersonal and intrapersonal skills with an impact on participants’ motivation,

involvement, and learning. They are related to the participants’ idiosyncratic

character and influence participation. In fact, Squires (1999) suggested the need to

design for freedom and flexibility so that educational software can adapt to their

idiosyncratic needs and styles.

Tutors-learners and learners-learners interactions were investigated using social

network analysis on a macro level across the network and on a micro level within

small groups. The interaction speed was high when the e-tutors were involved,

indicating control of the speed of the information flow. An implication is to delegate

control in interactions to e-learners in order to stabilise the interaction speed. This is

because the differences between the participants are minimised. In social networks,

information flow is relevant to issues of productivity, innovation and the classification

of useful ideas (Wu et al., 2004). Controlling and delegating interactions can be

connected to controlling or delegating e-learning (Dron, 2007:63). Decentralising the

power in a network increases the possibilities for co-creativity and innovation within

an e-learning community. In addition, since interaction density was directly linked to

text richness, richness is a measure of the interactive learning process (Stahl, 2002).

Lastly, as the e-tutors created groups with similar behaviour around them, an

implication refers to simulating (cloning) e-tutoring via vicarious learning. The e-tutors

should adopt different learning and interaction levels and styles based on e-learners’

idiosyncratic character aiming for all learners to achieve their goals. Therefore,

technologies need to be able to adapt to individuals’ changing needs and situations.

Overall, social awareness and the development of the sense of belonging to a

community were only recently related to social intelligence. The latter has been

accepted as an important soft skill (Goleman, 2007) even though it was mentioned in

Thorndike (1920) as knowledge to manage social situations and ‘act wisely in human

relations’. An implication is linked to the collaborative learning strong socio-cultural

nature, thus social intelligence can be a significant factor for successful e-learning

communities. For example, social emotions require self-consciousness (Goleman,

2007:131) that can be with the creation of profiles, avatars and other tools aiming to

enhance presence and co-presence. Another implication is related to the new model

for distributed leadership implemented as public consultancy from governmental

organisations and business; anyone can participate in decision making by sharing,

voting and discussing ideas (e.g. Dell, http://www.dellideastorm.com).

The development of collaborative learning networks and shared practice has been

found to be themes for continuing professional development (e.g. Pickering et al.,

2007). First, communication and problem-solving skills were improved by the e-

learners’ interactions. They were evident in the more complex discussions at the end

of the course comparing to monologues as redundant messages at the beginning of

the course. The analytical framework of collaborative e-learning episodes (CeLE) and

the associated tool MessageTag managed to bridge methods and tasks and provide

simple to use and reliable assessment of the e-learning quality. An implication is that

increasing reciprocity can facilitate the transition from monologues to dialogues as

there are increasing clues as opportunities for critical engagement in dialogue. A

second implication is related to the e-tutors’ ability to guide the e-learners into the

journey of critical thinking and knowledge co-construction and then leave them on

their own capabilities.

Overall, there is a need to re-think e-learning processes and methodologies and

make an effort to engage participants in the learning process (Rodgers, 2007).

Educators and designers need to re-visit teaching and learning strategies and their

relationship to the level of e-learners’ engagement taking under consideration the

strong idiosyncratic character of e-learners’ interaction and engagement. The direct

implication leads to the different learning and interaction styles needed in e-learning

(Cooze & Barbour, 2007).

The use of new tools was found to support collaborative e-learning to an adequate

extent. The implications are related to the need for numerical and graphical

evaluation tools that demonstrate their purpose of use. Such tools can increase e-

learners’ focus, intensity, and persistence in social and learning interactions. E-tutors

can direct and control online discussions, discover e-learners’ weaknesses and

strengths, activate the lurkers with specific questions, aid in team building by

“bonding” the team, and record the discussion. From a design viewpoint, several

groups need to evaluate learning technologies and applications anchored in their

different personas such a novice and expert users (Faulkner, 2000) as e-learners as

well as developers and e-tutors. A pedagogical usability evaluation framework can be

used to evaluate usability and utility of new tools. Designers need to seriously

consider the social aspects of learning, formative and summative evaluation, and

facilitate e-learners increase control as in self-emerged collaborative learning (Dron,

2007; Anderson, 2007). Such tools need to function on multiple levels supporting

interaction for individuals, small groups and networks or as Anderson (2008)

suggested, employ social software. This implication depicts the limitations of current

interactive applications; in the recent Communication of the ACM journal, Hendler

and colleagues stress that ‘today’s applications are very early social machines,

limited by the fact that they are largely isolated from another’ (2008:65).

The interventions built the types of communities of practice discussed by Kanes and

Lerman (2008). This is because the social and learning aspect was anchored in

legitimate peripheral participation as in Community of Practice Type 1 (CPT1).

However, it created an opposing dynamic in the Greek educational system by

suggesting that the community needs to move forward and acquire the new

competencies and technologies for the 21st century. This creates a conflict within the

educational system as with Community of Practice Type 2 (CPT2) (Kanes & Lerman,

2008): ‘CPT2 is built around tension, conflict and discontinuity of practice and

production’. An implication is to consider conflict as changing behaviour that can

facilitate the community’s movement to another level.

A final implication for research was connected to triangulating the data via

quantitative, qualitative and social network analysis; 3 different research perspectives

can open possibilities beyond initial propositions and hypotheses. Overall, there is

room for research on usable, useful and reliable tools and evaluation techniques to

assess different levels and types of participation and critical thinking in

Future research directions

Some future directions are proposed on research, e-learning readiness for

organisations, e-learning, e-learning communities, and associated design.

• Research o Multidisciplinary research on the social, learning, and technical

aspects of e-learning activity.

o Ethnotechnology as a methodology to advance community members’

own practices.

• E-learning readiness o Institutions and organisations assessment for e-readiness on a

technical and pedagogical level.

o Soft skills as part of teachers’ training and professional development.

o Resistance to change as a longitude study of e-learning communities.

• E-Learning o E-learning management as a social as well as a learning process.

o The process of e-learning and the ways different learning styles

influence it.

o The e-learning styles in relation to social intelligence.

o The impact of the relationships between the Collaborative e-Learning

Episode’s attributes.

o Design for each of the Collaborative e-Learning Episode’s attributes.

o Design for learning objects and their re-contextualisation based on the

different critical thinking levels in Collaborative e-Learning Episodes.

o The relationships between personalised and collaborative e-learning

and their impact to e-learning quality.

• E-Learning Community o Community design, management, evaluation and development, and

the attributes that most facilitate e-learning to occur.

o The impact of the relationships between the Collaborative e-Learning

Episode’s attributes.

o Design for each of the Sense of e-Learning Community Index’s

attributes.

o Evaluation of participation and its impact on students’ performance.

o The impact of interactions in e-learning across a learning network,

within groups and on an individual level.

o The role of decision making and leadership in e-learning communities.

• Design o Multimodal interaction and interoperability between educational

technologies.

o Design to support personalised and community e-learning

environments.

o Design to support community management and evaluation.

o Tools based on numeric and graphical representation for formative

and summative evaluation.

o The role of pedagogical usability in facilitating e-learning.

o Specific pedagogical frameworks and design on associated tools.

The discovery of the mirror neurons as the neurons that enable the representation of

other humans in the brain, social intelligence, current e-learning research, the new

communication technologies and social software, as well as this study, indicate that

collaboration is part of the human nature. Building on collaborative e-learning

communities can ensure e-learning quality; collaboration is written into our DNA.

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Tools and Evaluation Techniques for Collaborative E-Learning Communities Appendices

This is the English version of the Appendixes.

In some occasions, only samples of the data are presented.

APPENDIX I: ONLINE COMMUNITY MANAGEMENT

A_I_1. Moderator’s Responsibilities - Interactivity Management

1. Information.

− Informative first page: Ensure that the community’s first page provides all

needed information to encourage and inspire the students to engage.

− Introduction of themes in collaboration with the students and the Students

Administration Office.

2. Registration system: Facilitate the registration process if necessary.

3. Welcome note: A welcome note inspires and encourages the students to

participate as well as giving additional information on technical and management

issues (e.g. software description, inappropriate behaviour etc.)

4. Profiles: The students need to be encouraged to construct their profiles. Profiles

provide a feeling of co-presence and enhance the sense of belonging.

5. Induction and training: An initial meeting for using Moodle might bring issues of

usability of the system and suggest the problems students have on using the system

on site (if any). Additionally, information will be provided on ways for writing, replying

and form an online message.

6. Subgroups: Based on students’ research interests as well as hobbies sub-groups

will create initial locus of interactions.

7. Initial one-way communication: Introduction of the students (research interests,

hobbies, personal information that would like to share, experiences etc) as well as

tools (e.g. votes, polls, surveys, newsletters) can break the ice and give the

necessary information to move to two ways of communication and productive

interactions.

8. First message: The first of each student might define later behaviour. An initial

authentic reply and warm welcoming will encourage students to continue

communication as well as shy students to send a message.

9. Discussion highlights as newsletters: A monthly newsletter that will provide a

summary of the discussions and any additional information. Newsletters inform

members for news, activities, make members aware of the previous issues and

develop a felling of belonging to a community.

10. Motivation of silent participants: Moderatos need to ‘kick’ the students to

contribute to the community.

11. Monitoring and control: Subjects and discussions moderation could enhance or

prevent specific issues to be brought on the surface.

12. Use of the expert: Students might need more formal or expert advice in addition

to confidentiality that a community cannot provide.

13. Help and Support: The students need to feel that there is always someone there

on a 24/7 basis.

14. Give the members ownership of their learning and learning outcomes (work

behind the scene).

A_I_2. Suggestions for Writing Online Messages

Twenty five (25) messages (N=47, 53,1%) appeared to have a pattern: an initial

introduction as a response to the selected message, an extensive explanation and

justification of their point was made, an example was making suggestions very clear

and lastly, a greeting or an interesting quote used to ‘sign’ the message. A detailed

description is following:

1. Introduction, usually with an agreement with a previous message;

2. arguments and points of view;

3. an example to support the previous suggestions

4. stress of interesting points, more suggestions; and

5. signing out.

A second suggestion from Participant A1 in the e-mmersion study is as follows:

‘The lines in text on paper should, for the sake of readability not exceed 55-60 characters. On the screen lines should probably be even shorter. Then you get longer texts. According to Jacob Nielsen Internet user only skim webpages for headlines and marked keywords and they do it very fast. IMO this makes online communication and collaboration on sophisticated issues more or less impossible.’

APPENDIX II: RISK MANAGEMENT

The British Institute of Risk Management (IRM), the Association of Insurance and

Risk Managers (AIRMIC) and the National Forum for Risk Management in the Public

Sector (ALARM) (2002) have published a standard risk management procedure. Risk

can be defined as the combination of the probability of an event and its

consequences (ISO/IEC Guide 73). Risk assessment found to be important for this

study after the initial findings on the absence of cooperation with the Greek

educational authorities as well as the absence of the Greek teachers’ participation in

collaborative activities. Risk management increases the probability of success and

also reduces the probability of failure and uncertainty. Even though it is usually a

continuous and developing process, it was only used for the specific purpose of

completing the course under the desirable circumstances. In other words, a shift to a

different research context was not desirable.

Risk description was based on risk analysis, identification, description, and

estimation as well as risk reporting and decision making.

Risk Description

1. Name of risk • Absence of cooperation between the Greek educational authorities • Absence of participation in collaborative e-learning for 3 years

2. Scope of risk

• The Greek educational authorities may have provided a document to facilitate the conduction of the research, however, it cannot ensure that the stakeholders can take actions to support this study. • The Greek teachers’ absence of participation in collaborative e-learning activities does not mean that they will not cooperate in the study; fieldwork suggested that if they were given the adequate help and support they will.

3. Nature of risk • Operational • Knowledge management

4. Stakeholders

• The computers engineers that provide the technical support do not have any additional benefits if they implement the proposed tools other than some publications in their CV. In addition, their contracts have not been renewed which indicates a negative motivation to conduct extra work. • The Greek teachers can acquire knowledge on the pedagogical use of new technologies. Two certificates can be provided by London South Bank University and the Greek School Network, used for their professional development.

5. Quantification of Risk

• Situated implementation in a real environment is the ultimate goal for this study. However, it seems that this is not possible to be done under the specific circumstances. In

Based on the risk description, it appears that in the first case of implementing the

tools in the real e-learning environment developed for the Greek teachers the risk is

very high. Despite the fact that the Deputy Director of the Greek School Network

Technical Support said that the tools will be implemented, the risk estimation is 95%.

(A high risk is usually more than 25%). This is because cooperation with the Greek

educational authorities found to be 0% on more than one occasion. However, in the

second occasion of supporting Greek teachers in e-learning the risk is very low, less

that 2%. This is because the chance of enabling participation is considered to be

more than 75%.

The above description and risk estimation suggest that a shift to the study from a real

implementation to a quasi experimental one cannot completely alter the results and

significantly affect reliability and validity. In other words, the Hawthorn effect is

always a threat in research either in real or experimental environments. Having a

addition, it is not certain that finding a different environment can solve this problem. • Collaborative e-learning is the pedagogical goal of this study and it is highly likely to achieve it. The advantage of having an inactive community for 3 years is the increase of reliability and validity of the study. In addition, this study has a national Greek character and this is another advantage for the study as well as for me as being a Greek teacher.

6. Risk Tolerance • Not implementing the tools in a real and situated environment can turn the study to quasi experimental. • Not participating in collaborative e-learning will be a failure of the suggested propositions in total.

7. Risk treatment and control mechanisms

• There is nothing that can be done to change the situation for the computer engineers as this project is not part of their everyday work. • The Greek teachers can be taught and supported towards collaborative e-learning.

8. Potential action for improvement

• An alternative environment linked to the e-learning environment at the Greek School Network can be a middle solution. The study conducted in a research pool cannot not be completely experimental if linked to the real one; another is the Internet nature. (Studies on the internet are highly unlikely to be completely controlled.) • Theory and fieldwork suggested that if appropriate conditions are in place then absence of participation can be eliminated.

9. Strategy and Policy Development

• A server is needed to host the research pool • Initial work on instructional learning is acquired by producing documents on the use of the e-learning environment as well as collaborative e-learning. Continuous help and support can reduce participants’ uncertainty.

linked research pool can be the implemented measure to tackle the first risk;

provision of adequate help and support based on initial instructional learning and

then shift to collaborative e-learning can be the risk treatment for the second risk of

absence of participation.

APPENDIX III: INITIAL QUESTIONNAIRE (SAMPLE)

A_III_1. The usability section in the Initial Questionnaire

APPENDIX IV: QUESTIONNAIRE MAIN STUDY I (SAMPLE)

A_IV_1. Demographic data

APPENDIX V: QUESTIONNAIRE MAIN STUDY II

Dear colleague user,

Your contribution to this research is more valuable. The information you will provide will provide a process for the Greek teachers’ active participation in the online community and will reduce the time of engagement. In addition, your opinions and propositions will present existing e-learning problems. The information you will provide are strictly confidential and will only be used for research purposes. The results from this study will be available to you after its completion (September 2007). Despite the fact that the questionnaire is rather long, there was an effort to be easy to answer, with accuracy and speed in 30 minutes. It is consisted of the following 5 sections: Α. The e-learning community Β. Participation in the e-learning community C. Learning in the e-learning community D. New tools’ use and usability Ε. Professional development The questionnaires should be sent to Niki Lambropoulos until the 15th of April 2007 the latest, at the email nikilambropoulos@gmail.com You can use this text box to write your name and address in Greece in order to send you the certificates of participation from London South Bank University and the Greek School Network. They will be sent after all questionnaires are sent, late April 2007 the latest. Thank you very much for your participation. Best regards, Niki Lambropoulos

FINAL QUESTIONNAIRE You are invited to dedicate some of your precious time to fill in the following questionnaire. You can fill it in the way you prefer as there are not right and wrong answers –only different pinions-; therefore some questions are not very clear. The questionnaire was based on Word Processor form function; you simply click in the grey areas and select one of the answers (unless stated otherwise) on a scale from 1 (low) to 5 (very much) or simply write. The selection Don’t know / Don’t answer is referred as N/A.

Α. THE E-LEARNING COMMUNITY 1). How many people did you know in person before the online course? (a) Nobody (b) A few (c) Almost everyone (d) N/A 2). Do you think there was community development in time on the online course? (a) Yes (b) No (c) N/A 2ai. If you think community development was evident, can you describe some elements that prove it? 2bi. How did the discussion forums help/restrict the development of a sense of belonging to the e-learning community? 2ci.Was it comfortable or uncomfortable to talk to an online environment? 3). Did you develop any relationships, either friendly or professional with the other co-learners? (a) Yes (b) No (c) N/A 3ai. If yes, do you think they will continue outside the online course? (a) Yes (b) No (c) N/A 4). In your own opinion, what was the element that hold the community members together, if any? 5). In your own opinion, most of the participants shared their values. (a) Yes (b) No (c) N/A 6). In your own opinion, most of the participants had common interests and goals. (a) Yes (b) No (c) N/A 7). How much do you think that the members were helping each other in the online course?

(a) Very (b) Not much (c) A little (d) Almost no help (e) N/A

8). How long (in days) do you think it took for the community to emerge – develop a sense of working together?

9). Was the sense of being together strong? (a) Yes (b) No (c) neither yes or no (d) N/A

10). Do you think that... 1 2 3 4 5

a ...you knew what another person was feeling when you were reading her/his message?

b ...you could feel what a person was feeling when you were reading her/his message?

c ...you took an action upon it?

11). Do you agree or disagree with following statements: 11i. I can trust most of the participants. (a) Yes (b) No (c) N/A 11ii. Somebody has to be very careful in the online course because some participants wanted to take advantage of people and situations. (a) Yes (b) No (c) N/A 11iii. Most of the participants were trying to help. (a) Yes (b) No (c) N/A 11iv. Nobody trusted no one as regards knowledge exchange and contribution. (a) Yes (b) No (c) N/A

1 2 3 4 5

In a scale from 1-5, where 1 means very little and 5 a lot, how much do

you thin the participants trusted each other in the online course?

Very Small extend

Small extend

Neither

Great extend

Very great extend

a Individuals who had similar specialisation

b Individuals who had similar writing skills

c E-tutors

d Individuals who seemed to have advanced knowledge on the subject

e You cant trust anyone

13). In general, do you think that the level of trust during the online course: (a) Increased (b) Decreased (c) Remained the same (d) N/A

Β. PARTICIPATION IN THE E-LEARNING COMMUNITY

14). Do you think that... 1 2 3 4 5

a ...you knew the community’s netiquette for proper interaction?

b ...you knew the kind of community you were participating? c ...you liked to work together with the other members? d ...you felt free to express yourself? e ...you participated actively in the discussions?

f ... the e-learning management system helped the e-learning community?

g ...the new tools helped the e-learning community? 15). Do you think that YOUR participation was useful to the e-learning community? (a) Yes (b) No (c) N/A 15ai. If YES, can you describe why? 15bi. If NO, can you describe why not? 16. After your registration to the online course, from whom did you learn issues that were of your interest? 16a After your registration to the online course, how did you learn issues that were of your interest? Can you describe some ways? 17). Do you thin that there were roles developed between the members? (a) Yes (b) No (c) N/A 17ai. If YES, what were these roles (please give an example)? 18. Do you think that active participation is necessary?

(a) Yes (b) No (c) N/A 18ai. If YES, why?; 18bi. If NO, why not? 19. Do you think that the members who DID NOT participate actively had to remain in the course? (a) Yes (b) No (c) N/A 20). Do you think that new members in the e-learning community can contribute to existing knowledge? (a) Yes (b) No (c) N/A 20a. If YES, in what ways? 20β. If NO, why not? 21). Do you think that cooperation with other professional communities (e.g. programmers, multimedia developers, etc) is necessary? (a) Yes (b) No (c) N/A 21a. If YES, why? 21b. If NO, why not? 22). The participants were specialised in different areas. Do you think that this helped collaboration in the online course? (a) Very (b) Not much (c) A little (d) No (e) N/A

C. LEARNING IN THE COLLABORATIVE E-LEARNING COMMUNITY

23). Did you learn ways to enhance collaboration using new tools in the online course? (a) Yes (b) No (c) N/A

23a.. If YES, how did you learn them?

24). What were the most important examples of collaborative learning for you?

25). Who did you MOSTLY turn for help when you faced some problems? (a) to the e-tutors (b) to other e-learners (c) nobody (d) to a different resource (e) N/A

D. NEW TOOLS’ USE & USABILITY

26 Frequency for using the tool in Moodle... 1 2 3 4 5

a Participation – participation graphs and Avatar b Kind of reply – message tag in reply c Sociogramme VIT Nodes d Sociogramme VIT Centrality

27 Did you think that the tools was attractive? 1 2 3 4 5

28 Was the additional information with the new tools on Moodle tiring? 1 2 3 4 5

29 How would rate the quality of the graphics? 1 2 3 4 5

30 Did you think that the tool design was functional (easy to use)? 1 2 3 4 5

31 How would you rate the originality of the tool? 1 2 3 4 5

a Participation – participation graphs and Avatar

b Kind of reply – message tag in reply c Sociogramme VIT Nodes d Sociogramme VIT Centrality

32 Were the instructions on the tools satisfactory? 1 2 3 4 5

33 Did you think that learning how to use the tool is time consuming and tiring? 1 2 3 4 5

34 Did you think that accessibility of the tool was easy? 1 2 3 4 5

35 Were there any failures to complete an activity because of tool failure? 1 2 3 4 5

36 Did you think that the tool responded relatively quickly? 1 2 3 4 5

37 Did you think that the tool responded to the educational goals? 1 2 3 4 5

38 Did you think that the tool enhanced motivation for 1 2 3 4 5

communication and collaboration? a Participation – participation graphs and Avatar b Kind of reply – message tag in reply c Sociogramme VIT Nodes d Sociogramme VIT Centrality

39 Did you think that the tool was effective to facilitate collaborative learning? 1 2 3 4 5

40 How satisfied were you using... 1 2 3 4 5

1) Ε. PROFESSIONAL DEVELOPMENT WITHIN CoP

41. Which one of the statements describes the common space between discussions and your own educational practice? Please choose accordingly (more than one answers are allowed): (a) I brought ideas/information from my job to the discussions

(b) Some e-learners provided information that made me think on my educational practice (c) Some e-learners provided information that triggered ideas for my educational practice (d) The discussions will not change my educational practice (e) I found ideas/information I can use in my educational practice (f) Other If Other, can you describe what is was? 42. The best thing(s) in my participation in the study was… 43. The worst thing(s) in my participation in the study was… 44. How many times have the educational authorities from the Greek Ministry of Education contacted you to ask your opinion on learning technology issues?

(a) Many times (b) Some times (c) A couple of times (d) Never 45. How many times have the educational authorities from the Greek Pedagogical institute contacted you to ask your opinion on learning technology issues? (a) Many times (b) Some times (c) A couple of times (d) Never 46. Do you have any other comments?

Did you have any problems with the questionnaire?

You can use this space for more comments and observations:

OBSERVATION REPORT No.

Name (Optional)

Description of activity Comments

Please check whether you have replied to all questions. Thank you very much for your participation in the study. Niki Lambropoulos Research Student, Centre for Interactive Systems Engineering Faculty of Business, Computing and Information Management London South Bank University, London, United Kingdom http://www.lsbu.ac.uk/bcim/research/cise/ * http://nikilambropoulos.org & 1 Dale Grove London N12 8EE U.K. Tel: +44(0)2084465909 Email: nikilambropoulos@gmail.com * niki@intelligenesis.homechoice.co.uk Skype: niki.lambropoulos

APPENDIX VI: PARTICIPANTS’ DOCUMENTS

Only samples from the participants’ documents are presented here; these were the

following:

A_VI_1. Invitation to the study

A_VI_2. Netiquette

A_VI_3. Instructions of use Moodle and the Research Pool

APPENDIX VII: THE E-MMERSION DATA ANALYSIS

A_VII_1. Demographics

Demographics

Variables Values # Participants Percent 20-30 7 22.6 30-40 10 32.3 40-65 14 45.2

Missing 0 0 Female 12 39

Male 19 61 2 Gender Missing 0 0

1-5 11 35.5 6-10 5 16.1

11-20 11 35.5 40+ 4 12.9

3 Working Experience

Missing 0 0 1-5 4 12.9

6-10 14 45.2 11-20 10 32.3

20+ 3 9.7 4 Use of computer

- software

Missing 0 0 No use 1 3.2

1 -2 h 17 54.8 3-5 h 6 19.4

6-12 h 4 12.9 12+ h 3 9.7

5 Use of new technologies in class: h/w

Missing 0 0 No use 0 0

1 -2 h 13 41.9 3-5 h 8 25.8

6-12 h 5 16.1 12+ h 5 16.1

6 Use of new technologies for education: h/w

Missing 0 0 No use 1 3.2

1 -2 h 21 67.7 3-5 h 4 12.9

6-12 h 2 6.5 12+ h 3 9.7

7 Use of Internet in class: h/w

Missing 0 0 No use 0 0

1 -2 h 8 25.8 3-5 h 8 25.8

6-12 h 11 35.5 12+ h 4 12.9

8 Use of Internet for education: h/w

Missing 0 0 0 12 38.7

1-5 16 51.6 6-10 2 6.5 9 Use of LMS

Missing 1 3.2 Simple 7 22.6

OK 19 61.3 Difficult 2 6.5

N/A 2 6.5 Other 1 3.2

10 Moodle (std.d: 0.92)

Missing 0 0

A_VII_2. Crosstabulation: Internet Use in class * Use for educational purposes

Internet use for educational purposes (h/w) 1 -2 h 3-5 h 6-12 h 12+ h Total

no use 0 1 0 0 1 1 -2 h 8 4 8 1 21 3-5 h 0 2 1 1 4

6-12 h 0 0 1 1 2

Internet use in class (h/w)

12+ h 0 1 1 1 3

Total 8 8 11 4 31

A_VII_3. Crosstabulation: Moodle Use * Time using LMS

Time using LMS (years)

0 1-5 6-10 nil Total

Simple 4 2 1 0 7 OK 6 11 1 1 19 Difficult 1 1 0 0 2 Don't Know 1 1 0 0 2

Moodle Use

Other 0 1 0 0 1

Total 12 16 2 1 31

E-Learners' perseptions onMoodle usability level

7, 24%

18, 62%

EasyOKDifficultDon't Know

Missing: 1

A_VII_4. Moodle Usability

A_VII_5. Training in Educational Technologies

Training in Educational Technologies

Training locus # Participants Percent 1 Old academies 1 3.2 2 Universities 4 12.9 3 Postgraduate studies 4 12.9 4 Courses 14 45.2 5 N/A 4 12.9 6 Other 4 12.9

Total 31 100.0

A_VII_6. Reasons for participating in e-learning communities

A_VII_7. Use of e-learning tools

Web Design Pool:

A_VII_8. Messages Quantitative Analysis

MESSAGES QUANTITATIVE ANALYSIS

Forums Topics Threads Depth Richness of text (# words) Date

(P) 4/5 522 30/03-11/04/06(P) 2 302 27/03-09/04/061 Ask the expert 3 (P) 2 233 30/03-09/04/06

4/8 59 27/03-07/04/06(P) 10 838 03-05/04/062 Problems 3/6

2 48 27/03-04/04/06

3 Quality in Education 1/5 6/7 558 29/03-10/04/06

5/5 282 29/03-03/04/064 Hypertext - Url 2 6/6 247 27-31/03/06

5 Files management 1

6 Files characteristics 1

7 Navigation 1 4/4 863 28/03-03/04/068 Menu 1 3/3 431 28/03-15/04/06

9 Website Plan 1 4/4 495 28/03-12/04/0610 > left-right click 1 4/4 138 28/03-12/04/06

(P) 3/3 235 27/03-04/04/0611 Layout 2 (P) 112 Colour palette 1 2/2 146 28/03-12/04/06

(P) 3/3 108 27/03-15/04/073/3 115 29/03-12/04/0613 What to avoid 3

214 Hosting 1 6 538 03-12/04/06

Total 14 23 73 6,158 27/03-15/04/06Per day 0.7/d 1.2/d 3.8/d 324.1/d 19 days

A_VII_9. Forums and users view log files

LOG FILES (27/03-15/04/2006 – 19 days)

Type of View Views Average per day Percent on total views (2,493)

1 Forum view discussion 758 39.9 30.42 Forum view forums 61 3.2 2.43 Forum view forum 567 29.8 22.74 Forum add post 73 3.8 2.95 User view all 59 3.1 2.46 User view 171 9 6.9

Total 1,689 88.9 67.7

A_VII_10. Participation in e-learning Communities

A. Active Participation in E-Learning Communities Importance # Responses Percent 1 Yes 29 100 Missing 2 6.2

Reasons

1 Knowledge exchange – active learning 8 27

2 The community can exist 6 20

3 Responsibility for own learning & self-esteem 3 10

4 Learning is more interesting 1 3

5 Problem solving 1 3 6 Achieving learning targets 3 10 7 Collaborative learning 5 17 8 Win-win situation 1 3 9 Expands learning further 2 7

10 N/A 1 3.2 Missing 4 12.4

B. Time to Develop a Sense of Community Time Responses Percent 1 1-2 days 18 58 2 3-4 days 2 6 3 5-7 days 3 10 4 Up to 2 weeks 3 10

5 I don’t feel part of the community 5 16

Missing 0 0

A_VII_11. Online course experience

Online Course Experience Reasons Responses # Responses Percent

Learning in e-learning 6 18 Interesting & useful

experience 4 12

The new tools 3 9 Interaction and participation 12 37

The course was in Greek 1 3 e-learning community 1 3

Time issues for course organisation 1 3

New ideas 2 6 Participation in e-learning

research 2 6

My limitations in the use of ICT 1 3

1 The best thing was...

Total 33 (28/31) 100 Unclear instructions 2 14

Lack of time 7 51 Technical problems 2 14

The course was short 2 14 Fear of unknown 1 7

2 The worst thing was…

Total 14 (14/31) 100 Exciting experience 1 5

Life-long learning 2 9 e-learning is the future 1 5

New approaches 1 5 Low implementation 1 5

More e-learning initiatives 2 More evaluation &

feedback 4 17

Better implementation of the tools 4 17

Better e-learning quality in Greece 3 14

More chat use 1 5 More Moodle usability 2

3 More comments

Total 22 (6/31) 100

A_VII_12. Messages Analysis: Collaborative E-Learning Episode I COLLABORATIVE E-LEARNING EPISODE I

Levels of Abstraction CeLE parameters #Codes Indicators #References

Info, statement, definition 57 Social cues (nice behaviour, thanks, greetings) 19 Question 32 Url 24 Problem 20 Bullet points 11 I think, I believe 9 Instruction 7 I know, have worked 5

1 Initiation: Question - Information 9

Image 1

Individual solution 28 Example, further explanation 23 Because, this is why, thus, therefore 3 2 Explanation 4

Help 3

Yes, I agree, you are right, same 9 Refer-to-a-name for agreement 7 3 Agreement 3 It is very interesting 1

But, however, on the contrary 7 3a Conflict 2 Disagreement, different 7

If, might, could, would, should, think 18 Suggestion 4 I have an idea, something else, what do you mean 3

4 Exploration 4

alternative 2

Best, it is important 23 Comparison 15 Worst, unfortunately, no meaning 7 I prefer 3

5 Evaluation 5

Easiest 3

Mutual solution 4 6 Ideas, Co-construction 2 Overall, we agreed, finally 3 7

7 Other 1 Emphasis (colour, bold etc) 25 25 TOTAL 30 376

A_VII_13. CeLE 1 (AIa-1:stanzas1-25)

Introduction

Ask the expert! Sophi

Danis answers your questions

a How we can create a website in two or more languages? 1. Spyros Papadakis 5 Tue, 11 Apr 2006, 11:02 PM

Spyros Papadakis 5 Tue, 11 Apr 2006, 11:02 PM 30 Re: How we can create a website in two or more languages? by Antoniou Konstantinos - Thursday, 30 March 2006, 09:10 PM

> Re: How we can create a website in two or more languages? by Sophi Danis – Friday, 31 March 2006, 07:26 PM

Re: How we can create a website in two or more languages? by Niki Lambropoulos - Friday, 31 March 2006, 09:37 AM

Re: How we can create a website in two or more languages? by Damian Damianopoulos - Sunday, 9 April 2006, 09:51 PM

A I a 6 (1+5)

> Re: How we can create a website in two or more languages? by Mary Frentzou - Tuesday, 11 April 2006, 11:02 PM

Tools & Evaluation Techniques for Collaborative E-Learning Communities Chapter 6: Main Study

Participant SP1 started with a question as the title of the discussion (AIa-1:stanza3). Discussion Title: How we can create a website in two or more languages? Participant SP1 elaborated the subject and indicated the aim of the discussion (AIa-1:stanza4). I want to make a website in Greek and English (or and more) Languages. It was followed by 2 questions (AIa-1:stanzas5-6). - Which techiques are the best in this case. - Are there any templates available? Then the first message ended with participant’s name (social cue) (AIa-1:stanza8). Spyros There were five responses from AK1, SD1, NL1, DD1 & MF1. Response 1 (AK1). The first was an explanation with an example (AIa-1:stanza14). The only way I know is having a template and then editing-translating the content and the buttons. This site (website) has great templates, but you ought to have some experience with Photoshop to edit them. Then there was a reference to AK1’s experience and evaluation took place by referring to best practice and justification of the evaluation (AIa-1:stanza14). I prefer this way, because I don't have to code or design my webpages from scratch. A second initiation took place providing further information (AIa-1:stanza15). Other web sites offer templates in html format, A conflict stressed a comparison and initiated justification for best practice (AIa-1:stanza15). but I'm a little bit lazy and want to get the best results with little effort, so I prefer Photoshop file format Participant AK1 closes his message with an emoticon declaring satisfaction (social cue) (AIa-1:stanza15).

Response 2 (SD1). The answer from Participant AK1 was agreement based on the same interest and provision of more information as the initiation of his message (AIa-2:stanza18). This is a very interesting question, now we cooperate across countires, especially working on EU educational projects. Sometimes international websites contain a cookie that will search and detect the regional settings your computer is using and they will present the version that is compatible with those settings, including the country (regional settings)…. An alternative solution initiated the aim of the next verse by replying explicitly to SP1 (you) (AIa-2:stanza20) If, however, you want to design a webisite can be both Greek and English… Based on the previous Participant’s SP1 message explores the issue further (AIa-2:stanza20). tehn you will ahve to resort the translation of teh website and use,… Participant SD1 agrees with a previous message and refers to the name of the

person (social cue) (AIa-2:stanza20). as mentioned by K, templates;… Additionally, SD1 provides a different solution (AIa-2:stanza20). or alternatively, you can build your website and translae it, and use one css template for both. SD1 justifies and evaluates the proposition with a comparison referring to practical implementation (AIa-2:stanza20). This will make your job easire. SD1 closes the message by providing more information as well as evaluating the given information (AIa-2:stanzas22-24) More on CSS can be found here> http://www.w3.org/Style/CSS/ this is basic and some more http://www.developertutorials.com/css-2/cover.html Response 3 (NL1) The Researcher replied by exploring the issue further, explaining her solution on a project (AIa-3:stanzas27-28). The researcher tried to get involve in the discussions as minimum as possible. A different approach is the bilingual one. I built the Greek School of London website here <http://dim-lon.europe.sch.gr/> If does not work > (pic available) Response 4 (DD1) DD1 started his message by greeting the person who sent the initial question (social cue) (AIa-3:stanza30). Hi, S. He agreed with a previous message and provided his own individual solution (AIa-3:stanza31). Yes you can make a website in two or more languages. A good example is my personal home page (<http://users.ker.sch.gr/geoker>) Then he went into an exploration of SD1’s suggestions (AIa-3:stanza32). In order to produce an identical site in two languages DD1 compared and evaluated the suggestions (AIa-3:stanza32). it is best to produce the two templates from a single one. He explored and explained the suggestions further (AIa-3:stanza32). You must also use identical graphics, but in the different languages if the graphics involve speech (cf. site above). If you use FrontPage you can develop the corresponding pages in parallel. You can even perform exactly the same steps in the construction of the pages by toggling from one page to the other clicking on the relevant tab and perform the identical jobs. After exploring and explaining his suggestions, DD1 made an evaluation on a topic as regards the design (AIa-3:stanza33). It is best to give names to your files which facilitate grouping Then he provided a justification of this evaluation (AIa-3:stanza33). that is to group the materials which are needed for a page can have a common characteristic at the beginning.

He gave an example of best practice for further exploration (AIa-3:stanza33). For instance if I want to produce a page connected with Corfu I would give names like <corfu.htm> for the HTML page. The various graphics would have names like <corfu.banner.jpg>, <corfu.bottombanner.jpg>, <corfu.sidebarmenu.jpg>, <corfu.mainframe.htm>, if you see what I mean.

Lastly, he offered more help if needed (AIa-3:stanzas34). I should be glad to help more if you need any more specific details.

The he finished his message with a greeting and providing his name (social cues) (AIa-3:stanzas35-36). Cheers. D. Response 5 (MF1) MF1 adopted DD1’s style of structuring the message. The message has a greeting as an initiation; MF1 refers to a person from a previous message and ends the message in the same way, indicating empathic feelings reflected in her writing. MF1 started her message by greeting everyone (social cue) (AIa-3:stanza38). Hi everybody Then she agreed with DD1 referring to his name (social cue), the participant who sent the previous message (AIa-3:stanza39). I agree with D. MF1 evaluated his suggestions (AIa-3:stanza34). The way he describes is the easiest. Then she explored DD1’s solution with an example (AIa-3:stanza41). If you want to have both languages on the same page if you use frontpage (at least the older versions) you copy and paste <meta http-equiv="Content-Type" content="text.html; charset=iso-8859-7"> you insert it after the <head>. She tried to provide additional material but her attempt failed due to technical problems (AIa-3:stanza41). I tried to upload it as an attachment but it was impossible. Referring to previous participants’ solutions MF1 explored them by adding her suggestion (AIa-3:stanza41). Frontpage 2003 seems to recognize the languages automatically although I am not pretty sure beccause I haven't worked with it. Finally, she explored an alternative option to everything said up to now (AIa-3:stanza43). If you use dreamweaver you change the page properties to Greek (English is recognized automatically) Imitating DD1, MF1 she finished her message with a greeting and providing her name (social cues) (AIa-3:stanzas45-46). cheers M

A_VII_14. Participant SP1: Thought Processes

AIM – Q1 Q2 (AK1 ) explanation Example Evaluation (AK1 experience) Justification (reasons) Further Information Conflict to justify Aim Evaluation

APPENDIX VIII: CONDITIONS OF WORKING AND LEARNING ONLINE

TIME IN EDUCATION AND THE USE OF ICT IN ONLINE EDUCATION 0 years Months 1-5 years 6-10 years 11-20 years 20+ years N/A Time

Freq. % Freq. % Freq. % Freq. % Freq. % Freq. % Freq. % 1 Employed 2 5.0 10 25.0 18 45.0 9 22.5 1 2.52 Use Computers 3 7.5 14 35.0 15 37.5 7 17.5 1 2.5

1-3 2 5.0 3 57.3 Use LMS 22 55.04-6 1 2.5

13 32.5 1 2.537 92.5

Train in ICT No University Postgraduate ICT course Other Freq. % 1 3 7.5 2 5.0 4 10.0 29 72.5 1 2.5

Train in Moodle 1 26 65.0 2 5.0 1 2.5 8 20.0 1 2.5 2 05.

Time on the Internet All day Once–twice a day Every 3 days Freq. % 113 32.5 23 57.5 2 5.0 2 05.

USE & IMPORTANCE OF PROFILES AND FORUMS (LIKERT SCALE) Very Low Low Neither High Very High Freq. %

1 Use Profiles 3 7.5 1 2.5 9 22.5 6 15.0 8 20.0 13 32.5 Importance 2 5.0 1 2.5 9 22.5 6 15.0 12 30.0 10 25.0

2 Use Forums 0 0.0 6 15.0 4 10.0 8 20.0 13 32.5 9 22.5 Importance 0 0.0 1 2.5 5 12.5 9 22.5 17 42.5 8 20.0

APPENDIX IX: THEMATIC ANALYSIS IN THE MAIN STUDY

A_IX_1. Post-retreat opinions on participation

POST-RETREAT OPINIONS ON PARTICIPATION IN COMMUNITIES (N=34)

LEVELS Sub-levels Responses # Willing to participate 5 Collaboration / interactions 4 Sense of belonging / bonding 4 Situated problem solving 3 Evolution 3 Implementation of theory & methodology 2 Common goals / problems 2 Dynamic grouping 1 Visible in public 1 Provision of help 1 Coordination 1 Viability 1

Management

Encouragement 1 Information exchange 3 Quality 3 More interesting learning 3 Collaborative learning 2 Shared work experience 2 New knowledge building 2 Vicarious learning 1 Discovery 1 Common questions 1 Skills acquisition 1

Social & Learning Activities

Knowledge

New pedagogical approaches 1 New technologies 1 Tools Use Functionality 1

A_IX_2. Post-retreat opinions on e-learners’ participation in the project

POST-RETREAT OPINIONS ON E-LEARNERS’ PARTICIPATION (N=31)

On this community (personal involvement) On any community

LEVELS Sub-levels Responses # Responses #

Collaborative activities 4 Positive thinking 1Active participation 1 Active participation 1Dialogue 1 Transformation 1Communication 1 Continuity 1Contribution to the project 1

Management

Motivation 1 Provision of help 4 Everyone helps 2

Social activities

Contribution Own participation 2 Small stone to

community building 1

Target to learn 1 Following instructions 1 New challenges 1 Sharing abilities 1

Learning activities

Management

Participation in activities 1

Problem solving 1 Learn something interesting 1 Learn something useful on a personal level 1

Learn something useful on a community level 1

Implementation of new experience 1

Implementation of new knowledge 1

Participation in planning 1 Presentation of own experience/work 3 Discussions 1

Opinions 3 Ideas 1Questions 2 Opinions 1Information 2 Propositions 2 Discussions 2 Exploration 1 Comments 1 Advice 1 Suggestions 1 Answers 1

Knowledge

Use new tools 1

A_IX_3. Post-retreat opinions on new members’ contribution

Post-Retreat Opinions on New Members’ Contribution

LEVELS Sub-levels Responses # Active participation 4 Different problems / heterogeneous group 4 Interaction 2 Enthusiasm 5 Exploration 1 Viability / regenerates the community 3 New perspectives / abilities 2 Willingness to cooperate 1 Willingness to learn 1 Shared interest 1 Training 3 Frees the community / expression 2

Management

Feedback to older members 2 Shared ideas / knowledge 5 Fresh knowledge / ideas / experience 16 Knowledge transfer 3 Quality 1 Questions 4 Propositions 1 Criticism 1 Life-long learning 1

Collaborative e- Learning Communities

Knowledge building

Knowledge building 1 Tools Use Training in new technologies 2

A_IX_4. Post-retreat opinions on communities

POST-RETREAT OPINIONS ON COMMUNITY EVOLUTION

Evolution elements (N=38) What hold the community together? (N=40) LEVELS

Responses # Responses # Increasing interactivity / help 12 Common interests / goals 22 Communication outside and after the course 8 E-tutors 5

Common interests / goals 7 Desire for success 4 Online communication 6 Communication 4 Affective elements 6 Enthusiasm / being positive 3 Quick familiarisation 4 Willingness to collaborate 3

Increasing number of participants 4 Active participation / atmosphere 3

Communication – general 3 Subject 2 Collaborative atmosphere 2 Mutual help / trust 2 E-learners’ participation in planning 2 Reliability 1 Sense of belonging 2 Immediate success 1 Personal messages / experiences / first name 2

New colleagues 1 Photos 1 Visiting others’ web pages 1 Knew nobody initially 1

Social Level

Participation quality / quantity 1 Information & knowledge exchange 11 New knowledge / curiosity 12

Collaborative activities 8 Effective learning 3 Dialogue development 5 Projects development 2 Mobility of ideas 2 Collaborative learning 2 Learn to communicate 1 Willingness to learn 1 Vicarious learning 1 Immediate feedback 1 New skills acquisition 1 Problem solving 1

Learning Level

Number of created projects 1 Collaborative tools 4 New technologies 3 Tools Profile 1 Collaborative tools 2

A_IX_5. Post-retreat opinions on other communities

POST-RETREAT OPINIONS ON OTHER COMMUNITIES (N=34)

LEVELS Responses # Knowledge contribution / specialisation - reliability 12 Provision of directions 1 Multiple perspectives 9 Everybody wins 1 Effective problem solving 2 Users / teachers’ engagement - pedagogical issues 4 Individual development 8 Collaboration 1 Further development 3 Quality 1 Knowledge dissemination 2

Positive

Time saving 1

Simple interfaces are usable from all users so programmers are not needed 3 Negative Not following pedagogical approaches

Tools Need for technical infrastructure 2

A_IX_6. Post-retreat opinions on new members’ contribution

Post-Retreat Opinions on New Members’ Contribution (N=32)

LEVELS Sub-levels Responses # Active participation / interaction 6 Enthusiasm 5 Heterogeneous group 4 Training 3 Viability / regenerates the community 3 Frees the community / expression 2 New perspectives / abilities 2 Feedback to older members 2 Willingness to learn & cooperate 2 Shared interest 1

Management

Exploration 1 Fresh knowledge / ideas / experience 16 Shared ideas for knowledge building 9 Questions 4 Propositions 1 Criticism 1 Quality 1

Collaborative e- Learning Communities

Knowledge building

Life-long learning 1 Tools Use Training in new technologies 2

A_IX_7. Post-retreat opinions on learning

POST-RETREAT OPINIONS ON LEARNING

LEVELS Responses # E-tutors 30 Other learners 17 Own work 3

Whom (N=36)

More experienced members 3 Forums / chats 17 Emails / newsletters 16 Educational material 10 E-learning platform 6 Internet 4 Tools 4

How (N=37)

Search engines 3 Moderators 7 E-learners 6 E-tutors 5 Motivators 5 Leaders 4 Supporters 4 Technical support 2 Active participants 2

Roles (N=22)

Observers 1

APPENDIX X: COLLABORATIVE E-LEARNING EPISODES

(EXAMPLES FROM THE MAIN STUDY)

A_X_1. Collaborative e-Learning Episode III

CeLE-III was completed in one day (05/03/2007) and described the stages with

which P18 found the solution to a registration, problem based on her colleagues’

suggestions (CeLE-CIII: Stanzas 4-23). (Numbers on stanzas occurred automatically

in Atlas-ti™.)

CeLE-III Discussion Title: A different kind of question.

> P18 initiated the discussion with a statement about the exercise they had, that was creating a blog (stanza 5): I have created a blog in Pathfinder Then P18 describes her aim (stanza 5): but I would like to comment on Blogger. The steps P18 took (stanza 5): I created an account in Google P18 refers to the problem (stanza 5): but every time I log out [the system] it does not recognise the login name and password. Actions to solve the problem (stanza 5): I ended up having 3 accounts Result from actions: and I still have the same problem Question (stanza 5): I am doing something wrong, but what? Asking for help: Please help! > P24 asked P18 a question to clarify the problem (stanza 8): Do you add yourname@gmail.com for username? > E-tutor P32 explained what he had to do (stanza11): you simply write the user name you have from gmail > Then, R provided an example based on P24 and P32’s suggestion (stanza 14): e.g. login name: nikilambropoulso@gmail.com password: nbn3vb4325rb43wqbrliqwyfiuQGFLCBAf > E-tutor P52 asked more clarifying questions (stanza 17-18): Which blog do you want to use to comment? Are you allowed to post as administrator? Are the login name and password incorrect? > Then P52 asked for a following up on the process (stanza 18): Keep us updated on the process… > He finished his message with a social cue (stanza 18): pleaaaaaaaaase!

> P18 replied with a social cue (stanza 20): Thank you all for your help. > He found what the problem was (stanza 20): I found what was wrong with it. He explained what the problem was (stanza 20-22): When I first got the login name and password I wrote the mail address, not the user name and this resulted the system to ask for this address as a user name. The problem was solved (stanza 22): Now I can login. > P52 provided feedback (stanza 23): Bravo mate P18!! P52 sent greetings and thanked for the discussion (stanza 23): be well, thank you for the message.

Collaborative e-Learning Episode III: Analysis

A_X_2. CeLE-III Locus (CeLE-CIII: Stanzas 4-23)

COLLABORATIVE E-LEARNING EPISODE III: LOCUS

Section Forum

DiscussionReplies

Thread #

Words Total

A different kind of question - P18 - Monday, 5 March 2007, 01:59 PM

Re: A different kind of question - P24 - Monday, 5 March 2007, 04:54 PM

> Re: A different kind of question – P32 Monday, 5 March 2007, 06:25 PM

>> Re: A different kind of question – R Monday, 5 March 2007, 07:07 PM

>Re: A different kind of question – P52 Monday, 5 March 2007, 10:57 PM

>> Re: A different kind of question – P18 Monday, 5 March 2007, 11:12 PM

C I: Blogs in Education #29 7 (1+6)

>>> Re: A different kind of question – P52 Monday, 5 March 2007, 11:48 PM

A_X_3. CeLE-III Analysis

COLLABORATIVE E-LEARNING EPISODES Levels of Abstraction

CeLE parameters #Codes Indicators #ReferencesInfo, statement, definition, aim 3 Social cues (nice behaviour, thanks, greetings) 4

Social cue - help 1 Question 1 Aim 1

1 Initiation: Question - Information

Problem 2

2 Explanation 1 Example 1 1 Suggestion 2 4 Exploration 2 Question 3 5

5 Evaluation 1 Ask for result 1 1 Result 1 6 Ideas, Co-

construction 2 Bravo 1 2

TOTAL 12 21

A_X_4. CeLE-III Code Network: Initiation, Explanation, Exploration, Evaluation,

New ideas & Social cues

A_X_5. Internalisation and externalisation thought process

CeLE-III is relatively small (133 words) with more information on initiation and social

cues. The agreement and conflict stage was missed; three exploration levels were

built on participants’ questions. The following list represents the discussion in a linear

form as a collaborative problem solving process:

Initial post (P18): Statement – Aim – Problem – Question – Social cue (Help) (P24 ) Exploration (P32) Exploration: suggestion (R) Explanation: example (P52) Exploration – Initiation (P18) Idea – Social cue (P18) Evaluation: result (P52) Co-construction - Social cue This discussion is a Collaborative e-Learning Episode for a technical problem. The

discussion started with a message that initiated the aim and the problem to solve in

the discussion. A social sue attached an emotional level to the post (P18 seemed

desperate). Three interlocutors located the problem correctly using exploratory

questions as well as an example to help P18. It appears that P18 was based on

these suggestions, and managed to locate the problem and found the solution. This

was verified by P52’s social cues for feedback (bravo). Persistence for measuring

CeLE’s intensity seemed to be on a high level; the discussion was focused on the

particular problem.

A_X_6. Collaborative e-Learning Episode IX

CeLE-IX was completed in 3 days (29-31/03/2007) and referred to the use of specific

e-learning tools in the project creation process. The discussion was initiated outside

the online course between P37 and P22; then the participants shared their

proposition with the rest of the group (CeLE-GIX: Stanzas 2-84). (Numbers on

stanzas occurred automatically in Atlas-ti™.)

CeLE-IX Discussion Title: Implementing e-learning tools in Project Method.

> P37 initiated the discussion by presenting a proposition worked and agreed with P22 (social cue) (stanzas 2-9): After a conversation with P22 about the way e-learning tools can be implemented in the project method stages, we propose:

[The attached ppt image described an example using Web 2.0 and Web 1.0 tools: Free subject selection and initial design was related to videoconferencing; Research – information search and Elaboration was related to a blog; Synthesis – production was related to a wiki; Presentation was related to videoconferencing and a wiki; and Evaluation was related to videoconferencing and a wiki.] > O2 was an e-tutor. He replied the same day and tagged the message as INFORM (29/03/2007, stanzas 10-16). His points were directly disagreeing with P37 (stanza 12): I disagree with ‘Research – information search and Elaboration’ and with ‘Presentation’ as regards the use of tools. He provided two justifications (stanzas 13-16): In ‘Research – information search and Elaboration’ it is not the blog because I don’t conduct search with a blog or information elaboration but I record events, situations etc. In ‘Presentation’ it is not the wiki but the blog which I present my complete project. > P37 replied the next day (30/03/2007, stanzas 17-27).

She agreed (stanza 21): But this is exactly what is going to happen in a blog,

She explained the reasons for this decision with an example and stressed her opinion by highlighting and bolding the main points of her argument (stanza 21): recording and commenting of the data gathered and focused on events and situations for their elaboration. Obviously, I don’t do the search via a blog.

Then she explored the topic further and provided alternative points using bullet points (stanzas 22-27): The presentation in the World Wide Web using a wiki was [suggested] for the following reasons:

The whole tam will create the context and its contents The whole team will follow the stages before the final product The whole team will evaluate [the project] and will be evaluated And lastly it is recommended for navigation via the links, whereas the blog is somehow still – unless the presentation is very short.

> After 4 and half hours, she made a new proposition as continuing co-construction based on previous arguments (30/03/2007, stanzas 28-37): [This is] The advanced diagramme after the dialogue with O2: The blog is used only for data recording and commenting as regards events and situations gathered for further development. Search and data collection is conducted by the usual methods: Web, literature review, educational visits, discussions with specialists etc. In addition, the presentation can be done in a web-site, if we want to have more multi-media elements.

[The attached ppt image described an example using Web 2.0 and Web 1.0 tools: Free subject selection and initial design was related to videoconferencing; Research – information search and Elaboration was related to WWW, literature review and a blog; Synthesis – production was related to a wiki; Presentation was related to videoconferencing, a wiki and a website; and Evaluation was related to videoconferencing and a blog.] > P50 tagged his message as EXPLAIN (30/03/2007, stanzas 38-43). He agreed with P58 referring to his name(social cue) (stanza 40): I also agree with P58 He provided his own opinion as a co-constructive idea (stanza 41): And I believe that chat can be added in the first stage which is the friendliest, the most known in the community and its use could boost participants’ self esteem...... He signed off with his name (social cue) (stanza 43): P50

> (The following message was not on the logical order for the argument as reply to messages can be interrupted in discussion forums.) P58 tagged his message as QUESTION (30/03/2007, stanzas 48-50). He asked a question for all to agree (stanza 48): Do you agree that it is difficult to have videoconferencing on the first stage if we refer to a technologically illiterate audience? He explained his point with an example (stanza 49): Even this online course had to have videoconferencing in the third week… He provided an evaluation by exploring its negative aspects (stanza 49): It is not prohibiting but it can cause problems in the implementation… Lastly, he signed off with his initials (social cue) (stanza 50): P58 > P13 tagged his message as INFORM (30/03/2007, stanzas 53-58). He agreed with P58 referring to his name (social cue) (stanza 56): I also agree with P58. He explored P37’s argument referring to his name (social cue) (stanza 56): P37, it is very difficult to start the first stage with videoconferencing. He continued with an explanation and a co-constructive idea: I propose the division of the first stage in two sub-stages: Expression of interest and then on a separate basis the Design. Ideas to be project or having the potential to be projects can be announced via a database. There, anybody or a class or a school can write about their interests and using a search engine finding others with common interests. As for the medium of communication there could be emails and chat. This has been tested fro many years in Comenius and I think recently in etwinning with great success. Have a look on http://partbase.eupro.se/frameuk.htm as well.

After this can be proceeded then videoconferencing can be part of the design if needed.

He agreed with the previous message (stanza 56): As for the rest of the stages I agree.

He evaluated P37’s work referring to his name (social cue) (stanza 56): Anyhow, this was a great job, P37.

Lastly he finished the message with his first name (social cue) (stanza 58): P13. > P37 tagged his message as EXPLORE and wrote its Greek translation in capital letters (ΔΙΕΡΕΥΝΗΣΗ) (30/03/2007, stanzas 59-74). He agreed with the previous messages (stanza 62): I agree with all previous speakers. He explored the argument further and provided and example based on individual experience (stanza 63): I just need to stress two parameters: 1) Our students are too familiarised with the new technologies. They wont face any problem at all with videoconferencing; on the contrary, this environment is very attractive for them. He was defensive on the initial ideal as the expression of an under construction proposition (stanza 64): 2) This diagramme presents only a proposition for the implementation and use of tools, especially web 2.0, we worked on and not all of existing tools.

> P14 kept the EXPLORE tag (30/03/2007, stanzas 66-74). He evaluated and agreed with P37’s work (stanza 68): Very good job P37. As you wrote in your magic phrase ‘it is just a proposition’. It is accepted and implemented if the situations, the teachers and the technology allow it. He summarised (stanza 69): We learned what Blogs and wikis are and how to use them. He further explored the subject by questioning and evaluating previous statements (stanza 69): Fine, the important thing is the ways we are going to implement and taking advantage of them. Then he co-constructed an idea based on previous statements (stanza 70): In other words, would it be ‘very erratic’ if we thought for example that as regards an issue in a Blog or wiki our students knowing and implementing brainstorming presented their ideas?For me, the issue is to start playing in the ‘field’ they like that is internet and new technologies. He thanked (social cue) P37 in advance (stanza 72): Since you created this wonderful presentation, could you send it to me via email?? Thank you. He finished the message with his full name (social cue) (stanza 74): P14 > P22 replied the next day and tagged his message as EXPLAIN. (It appeared that he was defensive in his message.) (31/03/2007, stanzas 75-84). He quoted the first part of P37’s message and stressed the fact that it was an initial idea by changing the size of the font as well as making it bold (stanza 79): After a conversation with P22 about the way e-learning tools can be implemented in the project

method stages, we propose:

He agreed with P37 (social cue) (stanza 80):

- At is appears in P37’s first post, this is just a proposition based on the tools we used in the online course, including skype and msn, tools that most of our students can easily use, and in many occasions, better than many of our colleagues.

He explored the argument further with bullet points (stanzas 81-84):

- On the question which tools somebody will use to design, develop and complete his work, this depends on the situation (students’ age, school, infrastructure, level, students’ mood, etc)

- The order we propose with the tools and its implementation it is not, and it can’t be in any way, neither strict nor unique. Each one said [that] it depends on what, how, etc.

- The positive thing is that the previous slide created an argument that lead to a creative dialogue, and this is the essence of the online course, it is not that insignificant that a month ago most of us did not know or heard about these tools, we hardly knew them and for sure we had never used them.

A_X_7. Internalisation and externalisation thought process

The following thought processes represent the discussion in a linear form as a

collaborative problem solving process:

Initial post (P37): Statement – Aim – Proposition (text and image) (O2 ) Disagreement (P37) Agreement – Explanation – Exploration (P37) New proposition / idea (P50) Explanation - New proposition / idea (P58) Question (P13) Agreement – Initiation – Explanation - New proposition / idea – Evaluation – Social cue (P37) Explore (P14) Evaluation – Agreement – Summarise – Exploration - New proposition / idea – Social cue (P22) Agreement – Exploration

Collaborative E-Learning Episode IX: Analysis

A_X_8. CeLE-IX Locus (CeLE-GIX: Stanzas 2-84)

COLLABORATIVE E-LEARNING EPISODE III: LOCUS

Section Forum

Discussion Replies

Thread #

Words Total

Implementing e-learning tools in Project Method. – P37 – Thursday 29 March 2007, 08:53 AM

Re [INFORM]: Implementing e-learning tools in Project Method – O2 Thursday, 29 March

2007, 10:51 PM

> Re: Implementing e-learning tools in Project Method – P37 Friday, 30

March 2007, 09:31 AM

>> Implementing e-learning tools in Project Method – P37 Friday, 30 March 2007,

01:48 PM

G II: VC in E-Learning

>>> Re [EXPLAIN]: Implementing e-learning 41

tools in Project Method – P50 Friday, 30 March 2007,

04:33 PM Re: [QUESTION] Implementing e-learning tools in Project Method – P58 Friday, 30 March 2007,

02:47 PM

> Re [INFORM]: Implementing e-learning tools in Project Method – P13 Friday, 30 March 2007,

08:48 PM

>> Re [EXPLORE]: Implementing e-learning tools in Project Method – P37 Friday, 30 March 2007,

09:40 PM

>>> Re [EXPLORE]: Implementing e-learning tools in Project Method – P14 Friday, 30 March 2007,

10:34 PM

>>> Re [EXPLAIN]: Implementing e-learning tools in Project Method – P22 Saturday, 31 March

2007, 01:38 PM

A_X_9. CeLE-IX Analysis

COLLABORATIVE E-LEARNING EPISODE IX

Levels of Abstraction CeLE parameters #Codes Indicators #References

MESSAGETAGs 3 Propositions 2 Social cues (nice behaviour, thanks, greetings, names) 8(+4)∗

Question 2 Links 1 Aim 1 Quoting previous message 1

1 Initiation: Question - Information

Images 2

MESSAGETAGs 2 2 Explanation 1 Example 3 3/2

Agree 3 Agree to all previous interlocutors 1 3 Agreement Agreement referring to a name 4 Disagree 1 3a Disagreement

(Conflict) Disagree with justification 3

MESSAGETAGs 2 Question 2 Suggestion, alternative solution 4 Individual experience 1

4 Exploration

Bullet points 1

5 Evaluation Evaluation 5 10

Negative evaluation 1 Best practice & justification 4 Result 1 New idea 4 6 Ideas, Co-

construction Summary 2

7 Other 1 Emphasis (colour, bold etc) 15 15

TOTAL Tagged 9.2% 76/7

∗The number in parenthesis refer to a reply to a specific person indicated by her name

A_X_10. CeLE-IX Code Network: Initiation, Explanation, Exploration, Other,

Evaluation, New ideas, and Agreement/Disagreement CeLE-IX appears to be rich in arguments (921 words), especially on initial

information, exploration as well as agreements and disagreements. New ideas and

knowledge construction seemed to be related with all CeLE stages as explanation

and evaluation were relatively rich. Even though the discussion started as a

disagreement on a previous agreed proposition between two participations, it

cultivated two series of arguments that were mostly based on explanations and

explorations in order to evaluate the previous comments and reach new knowledge

constructions. Both CeLEs diagrammes depict the process inside and outside the

individual as a personal monologue and simultaneously a dialogue with the other co-

learners.

It is interesting to note that the interlocutors were different individuals except P37

who appears to be on the medium activity level. The participation in the discussion

appeared as follows:

Appendix XI: Messages Quantitative Analysis

A_XI_1. Messages Quantitative Analysis in Moodle@GSN

Post Message Analysis in Moodle@GSN (01/03 – 31/03/2007 – 31 days) # Initiations

(add forum topic) Replies (add post) Richness of text (# words) Section Forums

Total Analysis Participants Total Participants

Discussion Depth

Total Introduction (01- 21/03/2007) 59 49 49 182 142 (40) 231 9,075 Timetable (01 – 28/03/2007) 45 15 7 112 80 (32) 127 1,654 Social networking (01-24/03/2007) 6 5 1 25 16(9) 30 354 Moodle (01-08/03/2007) 3 2 2 5 3(2) 7 260

A Introduction

Problems (01-08/05/2003) 47 26 22 101 70(31) 127 4,113 Total 5 160 97 81 425 311(114) 522 15,456

B Project Method Projects Archive (01-07/03/2007) 6 1 1 5 4(1) 6 142 Total 1 6 1 1 5 4(1) 6 142

Blogs (01-31/03/2007) 61 42 43 156 127(29) 198 7,110 Tools (03-12/03/2007) 8 3 3 7 7(0) 10 498 C Blogs Blog & HTML (05-12/03/2007) 3 1 1 2 2(0) 3 61

Total 3 72 46 47 165 136(29) 211 7,669 Problems (12-23/03/2007) 15 10 9 27 24(3) 37 1,055 Design (17-18/03/2007) 2 2 2 4 4(0) 6 116 Practicality (13-18/03/2007) 4 2 2 16 13(3) 18 856

D Wikis

Groups (18-24/03/2007) 9 7 7 25 22(3) 31 748 Total 4 30 21 20 72 63(9) 92 2,775

Technical Problems (16-22/03/07) 8 2 0 15 7(8) 12 303 E Videoconferencing Groups (18-23/03/07) 1 1 0 10 7(3) 16 94 Total 2 9 3 0 25 14(11) 28 397

Project ideas (01-06/03/2007) 4 1 1 2 3(0) 3 236 F Internet Cafe Other (01-18/03/2007) 4 2 2 4 2(2) 6 232 Total 2 8 3 3 6 5(2) 9 468

Overall 16 285 171 152 698 533(166) 868 26,907 Percentage per day 0.97 01/03 – 31/03/2007 – 31 days 9.1 5.5 4.9 22.5 17.1(5.3) 28 867.9

Percentage 95 participants 3 1.8 1.6 7.3 5.6 9.1 283.2

per participant Messages Density 2a/N(N-1) 2X868/95(95-1)=0.19

A_XI_2. Messages Quantitative Analysis in the Research Pool

Research Pool (25 – 31/03/2007 – 6 days)

# Initiations (add forum) # Replies (add post)Richness

of text (# words) Section Forums

Total Analysis Participants Total Participants

Overall (Analysis+

Participants) Total

News (28-30/03/07) 7 2 5 6 5(1) 7 999 G VC in E-Learning VC in E-learning (28/03-01/04/07) 9 8 4 70 70(0) 78 8,942

Overall 2 16 10 9 76 75(1) 85 9,941 Percentage per day 0.4 25 – 31/03/2007 – 5 days 3.2 2 1.8 15.2 15(0.2) 17 1,988.2

Percentage per participant 42 participants 0.4 0.2 0.2 1.8 1.79 2 236.6

Messages Density 2a/N(N-1) 2X85/42(42-1)=0.1 * My initiations were included as some participants’ messages were produced from these initiations. The tables present the first three quantitative variables, richness of text, depth of discussions, and messages density. (My posts are in

parentheses.) These tables describe the results in Moodle@GSN and the research pool. The first column describes the online course section, the

second column the forums and the dates these forums were introduced and completed. Then the replies are divided into initiations found in logs

as “add forum”, and the actual replies, found in logs as “add posts”. From these messages, the sub-columns present the total number of

messages, the messages for analysis as well as participants’ only messages. The last two columns show the overall number of messages

provided the initiations for analysis including my messages, and the participants’ messages, and the richness of text.

APPENDIX XII: MAIN STUDY DATA & REPORTS

A_XII_1. PEDAGOGICAL USABILITY – UTILITY RESULTS Frequency % Frequency % Frequency % Frequency % Frequency % Mean St.D. N/A

Graphs & Avatars 2 5 3 7.5 8 20 17 42.5 10 25 3.8 1 0 3.625 MessageTag 1 2.5 3 7.5 8 20 17 42.5 11 27.5 3.9 1 0 VIT Nodes 4 10 6 15 8 20 14 35 8 20 3.4 1.2 0

1 Instructions VIT Centrality 4 10 7 17.5 7 17.5 14 35 8 20 3.4 1.2 0 Graphs & Avatars 7 17.5 14 35 7 17.5 7 17.5 5 12.5 2.7 1.3 0 2.4 MessageTag 8 20 14 35 6 15 4 10 2.8 1.2 0 VIT Nodes 14 35 11 27.5 13 32.5 1 2.5 1 2.5 2.1 1 0

2 Frequency of use

VIT Centrality 16 40 12 30 9 22.5 2 5 1 2.5 2 1.3 0

Alignment with

Graphs & Avatars 1 2.5 1 2.5 14 35 16 40 8 20 3.7 0.9 0 3.5

educational goals MessageTag 1 2.5 1 2.5 16 40 13 32.5 9 22.5 3.7 0.9 0 VIT Nodes 4 10 3 7.5 16 40 10 25 7 17.5 3.3 1.2 0

3 VIT Centrality 4 10 3 7.5 16 40 10 25 7 17.5 3.3 1.1 0 Graphs & Avatars 1 2.5 1 2.5 13 32.5 17 42.5 8 20 3.7 0.8 0 3.475 MessageTag 1 2.5 1 2.5 13 32.5 17 42.5 8 20 3.8 0.9 0 VIT Nodes 7 17.5 3 7.5 11 27.5 14 35 5 12.5 3.2 1.3 0

Support collaborative e-learning

VIT Centrality 7 17.5 3 7.5 11 27.5 14 35 5 12.5 3.2 1.3 0

5 Learnability Graphs & Avatars 6 15 10 25 9 22.5 12 30 3 7.5 2.5 1.1 0 2.725

MessageTag 11 27.5 11 27.5 10 25 6 15 1 2.5 2.4 1.1 1 VIT Nodes 6 15 10 25 9 22.5 12 30 3 7.5 3 1.2 0 VIT Centrality 6 15 11 27.5 8 20 12 30 3 7.5 3 1.2 0 Graphs & Avatars

15 37.5

12 30 3.9 1 0 3.675

MessageTag 1 2.5 2 5 8 20 16 40 13 32.5 4 1 0 VIT Nodes 6 15 4 10 9 22.5 11 27.5 10 25 3.4 1.3 0

6 Accessibility VIT Centrality

9 22.5

10 25 3.4 1.3 0

Graphs & Avatars

6 15 3.4 0.9 0 3.4

MessageTag 2 5 4 10 13 32.5 16 40 4 10 3.47 1 1 VIT Nodes 4 10 5 12.5 11 27.5 10 25 9 22.5 3.38 1.2 1

7 Originality VIT Centrality

5 12.5

11 27.5

8 20 3.35 1.2 1

Graphs & Avatars

15 37.5

10 25 3.7 1 0 3.5

MessageTag 1 2.5 3 7.5 9 22.5 16 40 10 25 3.9 1 1 VIT Nodes 6 15 5 12.5 12 30 11 27.5 6 15 3.2 1.2 0

8 Motivation to participate

VIT Centrality

11 27.5

7 17.5 3.2 1.2 0

Graphs & Avatars

15 37.5

11 27.5

7 17.5

3 7.5 2.2 1.2 0 2.175

MessageTag 16 40 10 25 8 20 4 10 2 5 2.1 1.2 0 VIT Nodes 14 35 10 25 10 25 5 12.5 1 2.5 2.2 1.1 0

9 Information overload

VIT Centrality

5 12.5

1 2.5 2.2 1.1 0

Graphs & Avatars

19 47.5

5 12.5 3.65 0.8 0 3.375

MessageTag 1 2.5 14 35 18 45 7 17.5 3.75 0.8 0 10 Functionality

VIT Nodes 5 12.5 5 12.5 15 37.5 10 25 5 12.5 3.1 1.1 0

VIT Centrality

5 12.5

5 12.5 3 1.1 0

Graphs & Avatars

13 32.5

5 12.5 3.5 0.8 1 3.3875

MessageTag 1 2.5 1 2.5 15 37.5 17 42.5 6 15 3.65 0.8 0 VIT Nodes 5 12.5 4 10 15 37.5 9 22.5 7 17.5 3.2 1.2 0

11 VD: Graphics VIT Centrality

5 12.5

15 37.5

9 22.5

7 17.5 3.2 1.2 0

Graphs & Avatars

5 12.5

6 15 3.4

0.9 3.0875

MessageTag 1 2.5 2 5 16 40 13 32.5 7 17.5 3.65 1 1 VIT Nodes 5 12.5 8 20 13 32.5 10 25 4 10 3 1.1 0

12 VD: Attractiveness

VIT Centrality

7 17.5

13 32.5

4 10 2.3

Graphs & Avatars

19 47.5

0.9 0 1.85

MessageTag 22 55 12 30 3 7.5 3 7.5 1.7 0.9 0 VIT Nodes 18 45 13 32.5 4 10 3 7.5 2 5 2 1.1 0

13 Tool failure VIT Centrality

19 47.5

2 5 1.9

Graphs & Avatars

10 25 3.8

0.9 0 3.55

MessageTag 4 10 9 22.5 16 40 11 27.5 3.8 1.1 0 VIT Nodes 6 15 1 2.5 15 37.5 12 30 6 15 3.3 1.2 0

14 Fast response VIT Centrality

15 37.5

6 15 3.3

Graphs & Avatars

13 32.5

8 20 3.7

0.9 0 3.375

MessageTag 1 2.5 3 7.5 15 37.5 12 30 9 22.5 3.6 1 0 VIT Nodes 6 15 3 7.5 17 42.5 8 20 6 15 3.1 1.2 0

15 Overall satisfaction

VIT Centrality

15 37.5

9 22.5

6 15 3.1

A_XII_2. CORRELATIONS IN SPSS

A_XII_3. MOST IMPORTANT CORRELATIONS IN THE HIERARCHICAL CLUSTERING EXPLORER

USABILITY – UTILITY CORRELATIONS

Rank X axis Y axis Pearson’s’ r

Positive Correlations 7 VD: Attractiveness VIT Centrality VD: Attractiveness VIT Nodes 0.9818 Accessibility VIT Centrality Accessibility VIT Nodes 0.9779 Tool failure VIT Centrality Tool failure VIT Nodes 0.97710 Functionality VIT Centrality Functionality VIT Nodes 0.96111 Instructions VIT Centrality Instructions VIT Nodes 0.96112 Satisfaction VIT Centrality Satisfaction VIT Nodes 0.95513 Info overload MessageTag Info overload Graphs/avatars 0.94614 Failure MessageTag Failure Graphs/avatars 0.94415 Motivation VIT Centrality Motivation VIT Nodes 0.93016 Accessibility MessageTag Accessibility Graphs/avatars 0.91817 Education goals MessageTag Education goals Graphs/avatars 0.88318 Satisfaction MessageTag Functionality VIT Nodes 0.84319 Education goals VIT Nodes Originality VIT Nodes 0.81020 Education goals VIT Centrality Originality VIT Nodes 0.81021 Satisfaction VIT Centrality Functionality VIT Centrality 0.80122 Satisfaction VIT Centrality Originality VIT Nodes 0.80123 Satisfaction VIT Nodes Functionality VIT Nodes 0.79224 Support CeL VIT Nodes Motivation VIT Nodes 0.78825 Support CeL VIT Centrality Motivation VIT Nodes 0.78826 Satisfaction VIT Centrality Support CeL VIT Nodes 0.78427 Satisfaction VIT Centrality Support CeL VIT Centrality 0.78428 Education goals Graphs/avatars Functionality Graphs/avatars 0.78229 Satisfaction VIT Centrality VD: Graphics VIT Nodes 0.77730 Satisfaction VIT Centrality VD: Graphics VIT Centrality 0.77731 Originality VIT Nodes Functionality VIT Nodes 0.77132 Accessibility VIT Centrality Instructions VIT Centrality 0.76333 Originality VIT Nodes VD: Graphics VIT Nodes 0.75234 Originality VIT Nodes VD: Graphics VIT Centrality 0.75235 Satisfaction VIT Nodes Functionality VIT Centrality 0.75136 Fast response MessageTag Fast response Graphs/avatars 0.75137 Satisfaction VIT Nodes Support CeL VIT Nodes 0.74838 Satisfaction VIT Nodes Support CeL VIT Centrality 0.74839 Originality VIT Nodes Functionality VIT Centrality 0.74040 Learnability VIT Nodes Learnability Graphs/avatars 0.73741 Learnability VIT Centrality Learnability Graphs/avatars 0.73742 Accessibility VIT Nodes Instructions VIT Centrality 0.73343 Functionality VIT Centrality VD: Graphics VIT Nodes 0.72944 Functionality VIT Centrality VD: Graphics VIT Centrality 0.72945 Accessibility VIT Centrality Instructions VIT Nodes 0.72346 Functionality VIT Centrality VD: Attractiveness VIT Centrality 0.72247 Satisfaction VIT Nodes Originality VIT Nodes 0.72148 VD: Graphics VIT Nodes VD: Attractiveness VIT Centrality 0.71849 VD: Graphics VIT Centrality VD: Attractiveness VIT Centrality 0.71850 Satisfaction Graphs/avatars Education goals Graphs/avatars 0.71251 Support CeL VIT Nodes Originality VIT Nodes 0.71252 Support CeL Centrality Originality VIT Nodes 0.71253 Satisfaction VIT Nodes VD: Graphics VIT Nodes 0.71054 Satisfaction VIT Nodes VD: Graphics VIT Centrality 0.71055 Motivation MessageTag Motivation Graphs/avatars

Negative Correlations 1714 Satisfaction VIT Nodes Failure VIT Centrality -0.6001715 Learnability MessageTag VD: Graphics VIT Nodes -0.6031716 Accessibility VIT Nodes VD: Graphics MessageTag -0.6031717 Support CeL Graphs/avatars Functionality VIT Nodes -0.6051718 Satisfaction VIT Nodes Info overload MessageTag -0.6051719 Satisfaction VIT Nodes Info overload Graphs/avatars -0.6071720 Motivation VIT Centrality Info overload MessageTag -0.6081721 Satisfaction VIT Nodes Failure VIT Nodes -0.6091722 Motivation VIT Nodes VD: Graphics MessageTag -0.6111723 Satisfaction VIT Centrality Accessibility Graphs/avatars -0.6121724 Instructions VIT Centrality Frequency Graphs/avatars -0.6191725 Originality VIT Nodes VD: Graphics MessageTag -0.6201726 Motivation VIT Nodes Info overload MessageTag -0.6201727 Satisfaction Graphs/avatars Functionality VIT Centrality -0.6211728 Education goals MessageTag Accessibility VIT Nodes -0.6211729 Education goals MessageTag Accessibility VIT Centrality -0.6241730 Education goals Graphs/avatars Instructions VIT Nodes -0.6241731 Satisfaction VIT Nodes Accessibility Graphs/avatars -0.6281732 Motivation VIT Centrality Info overload VIT Nodes -0.6281733 Motivation VIT Centrality Info overload VIT Centrality -0.6281734 Satisfaction VIT Centrality Info overload VIT Nodes -0.6291735 Satisfaction VIT Centrality Info overload VIT Centrality -0.6291736 Education goals VIT Nodes Info overload MessageTag -0.6301737 Education goals VIT Centrality Info overload MessageTag -0.6301738 Support CeL Graphs/avatars Functionality VIT Centrality -0.6311739 Motivation VIT Nodes Info overload VIT Nodes -0.6321740 Motivation VIT Nodes Info overload VIT Centrality -0.6321741 Education goals Graphs/avatars Instructions VIT Centrality -0.6331742 Education goals Graphs/avatars Accessibility VIT Centrality -0.6361743 Support CeL VIT Nodes VD: Graphics MessageTag -0.6381744 Support CeL VIT Centrality VD: Graphics MessageTag -0.6381745 Instructions VIT Centrality VD: Graphics MessageTag -0.6411746 Education goals Graphs/avatars Accessibility VIT Nodes -0.6421747 Learnability VIT Nodes VD: Attractiveness VIT Centrality -0.6531748 Learnability VIT Centrality VD: Attractiveness VIT Centrality -0.6531749 Originality VIT Nodes Info overload MessageTag -0.6551750 Functionality MessageTag VD: Attractiveness VIT Nodes -0.6571751 Support CeL VIT Nodes Fast response Graphs/avatars -0.6571752 Support CeL VIT Centrality Fast response Graphs/avatars -0.6571753 Satisfaction VIT Nodes Failure Graphs/avatars -0.6651754 Instructions VIT Centrality VD: Graphics MessageTag -0.6721755 Info overload VIT Nodes VD: Attractiveness VIT Nodes -0.6761756 Info overload VIT Centrality VD: Attractiveness VIT Nodes -0.6761757 Accessibility VIT Centrality Learnability VIT Nodes -0.6871758 Accessibility VIT Centrality Learnability VIT Centrality -0.6871759 Education goals VIT Nodes Info overload Graphs/avatars -0.6881760 Education goals VIT Centrality Info overload Graphs/avatars -0.6881761 Accessibility VIT Centrality VD: Graphics MessageTag -0.6891762 Info overload MessageTag VD: Attractiveness VIT Nodes -0.6901763 Originality VIT Nodes Info overload Graphs/avatars -0.6981764 Learnability VIT Nodes VD: Attractiveness VIT Nodes -0.7121765 Learnability VIT Centrality VD: Attractiveness VIT Nodes -0.7121766 Info overload MessageTag VD: Attractiveness VIT Centrality -0.7191767 Accessibility VIT Nodes Learnability VIT Nodes -0.7291768 Accessibility VIT Nodes Learnability VIT Centrality -0.7291769 Info overload VIT Nodes VD: Attractiveness VIT Centrality -0.7471770 Info overload VIT Centrality VD: Attractiveness VIT Centrality -0.747

A_XII_4. THE BEST THING IN THE PROJECT

THE BEST THING IN THE PROJECT WAS… (N=39) E-learners

LEVELS Sub-levels Responses #

Common interests / goals 6 Communication / participation / work together 11

Sense of belonging to something greater 7 Community Management

Exchange of opinions 1 Implementation of acquired knowledge 2 Presentation of own experience / work 1 Educational material 1 Professional training 2 Feedback 1

Management

New interests 1 New ideas / knowledge 1

Learning

Knowledge buildingNew skills 1 New technologies 9 Working with new technologies 1 Tools Use Real-time evaluation 2 Excitement 1 Study Hawthorn effect Successful contribution 1

APPENDIX XIII: RECOMMENDATIONS

Recommendations for researchers

• Open communication channels

• Work on multidisciplinary frameworks to acquire coherent views of the

research context

• Use ethnotechnology to inform design

• Target human-human and human-computer interaction in e-research

• Use social network analysis to triangulate results from qualitative and

quantitative data analysis

• Use real-time evaluation for proactive, just-in-time, and reactive decision

making

• Use time-series design for formative and summative evaluation

• Ensure scalability of methods, tools, and techniques

Recommendations for e-learning engineers

• Open communication channels

• Get involved in multidisciplinary teams

• Acknowledge the post hoc nature of design in evolving situations

• Design for learners as users and users as learners

• Design for pedagogical usability and utility

• Design tools relevant to professional practice

• Offer pragmatic solutions

• Use learner-centred design sensitive to its context on a macro and micro level

• Evaluate design in real-time as circumstances evolve

• Involve all e-learning participants in design

• Acquire opinions from different levels of practitioners’ expertise

• Integrate design, use and evaluation in design

• Make visible and support social and temporal structures of social interaction

• Design for collaborative e-learning tools and activities to

o observe and analyse human-human and human-computer interactions

o support persistence and depth of discussions

o support increasing participation

o provide detailed and accurate reports for each e-learner

• Modify the tools in this study

o Calculation of participation levels based on the highest poster’s

responses

o Enable quoting

o Semantic and temporal arrangement of the “Reply” function in

discussion forums

• Use different methods for pedagogical usability testing specifically designed

for new tools

Recommendations for e-learning practitioners

• Plan for E-learning o Acknowledge the strategic use of collaborative e-learning

o Facilitate and moderate progressive discourse

o Tackle performance problems associated with personality traits

o Obtain a balance on personalised and social learning

o Support self-organised e-learning

o Plan and routinise collaborative activities as a process of increasing

participation

o Use available technologies effectively

• Plan for E-Learning Communities o Open communication channels

o Define stakeholders’ intentions and goals

o Create highly targeted and interactive courses to engage e-learners o Use community assessment o Enhance social networking to create learning opportunities

o Train e-learners how to work together

o Work towards the different levels of participation

o Allow time for getting-to-know activities

o Focus on development and maintenance of empathy and trust

o Keep the enthusiasm going

Recommendations for the Greek educational authorities

• Open communication channels o Create an inclusive environment to support cooperation between

national institutions and teachers

o Be proactive, just-in-time, and reactive in decision making

o Shorten decision making periods using new technologies

o Enhance participatory decision-making

o Create groups for research and development beyond administration

• Create policies to support e-learning quality o Create a central organisation to ensure quality in e-learning

o Train e-tutors and e-learners

o Provide quality short training cycles relevant to the Greek teachers’

profession on a life-long learning basis

o Provide opportunities for Ministry chairs to learn firsthand about the

benefits of e-learning and the changing nature of 21st century learning

o Incorporate e-learning in institutions to support employees’ life-long

learning

o Create opportunities for e-learning experts and e-learners

Glossary

Baseline: The observation of behaviour prior to any treatment designed to alter behaviour. Collaboration: A coordinated, synchronous activity as a result of a continued attempt to construct and maintain a shared conception of a problem. Collaborative e-Learning Communities (CeLC): Social aggregations that emerge in online courses when enough people carry on progressive dialogues for the purpose of learning. Collaborative E-Learning Episode (CeLE): A communicative discussion episode with a starting point, a transition and an end point that indicates a collaborative e-learning cycle. Collaborative Learning: The type of learning that takes place when learners work in groups on the same task using progressive dialogue for co-creativity. Community: A group of people who consciously share a sense of belonging anchored in common interests and enhanced by social interactions. An online community is a community where social interactions are facilitated by information and communication technologies. Communities of Practice (CoP): Groups of people who share a concern or a passion for something they do and learn how to do it better as they interact regularly. Decentralisation: The ability to take into account viewpoints of a given situation Empathy: A complex psychological inference in which observation, memory, knowledge and reasoning are combined to yield insights into the thoughts and feelings of others. E-Research: The research in online environments. Ethnography: The branch of anthropology that provides scientific description of individual human societies. Ethnotechnology: An ethnographic field for studying design in real environments. Grounding: Interactions intended to create mutual understanding, knowledge, beliefs, assumptions or repairing misunderstandings in a group. Heuristics: A form of usability inspection where usability specialists judge whether each element of a user interface follows a list of established evaluation variables. Human Computer Interaction (HCI): The study, planning and design of what happens when humans interact with computers. Informal learning: The unofficial and unstructured way of learning. Instructional Design: The systematic process of activities to solve an instructional problem with the aid of technologies. Instructional Engineering: The systematic process of activities to solve an online instructional problem anchored in Human-Computer Interaction.

Learner-Centred Design (LCD): The design that considers the learner/user as the center of instructional design. Learning Management System (LMS): A software package designed to manage learning interventions in technology enhanced learning. Legitimate Peripheral Participation (LPP): The process of social learning that occurs in Communities of Practice containing different levels en route for members’ engagement and practice. Lurking (Passive Participation): The activity of one of the "silent majority" in an electronic forum that involves posting occasionally or not at all but reading the group's postings. Mirror Neurons: The premotor neurons which fire both when an animal acts and when the animal observes the same action performed by another (especially of the same species) animal. Online Communities: Online social aggregations that emerge when enough people carry on those public discussions long enough to form relationships. Online Learning: A planned teaching and learning experience that uses a wide spectrum of technologies to reach learners at a distance. Pedagogical Usability: A quality attribute that assesses how easy learner/user interfaces are to use with a purpose of learning. Sense of e-Learning Community Index (SeLCI): The index to measure the sense of belonging in an e-learning community. Social Computing: The incorporation of sociological understandings into interface design aiming at building systems that fit more easily into the ways we communicate and work. Socio-cultural learning: A theoretical framework which emphasises the role of social interaction in the development of cognition. It supports that cognitive development is based on the negotiation of meaning that originates from individuals’ actual relationships. Social Network Analysis (SNA): The mapping and measuring of relationships and flows between people, groups, organizations, computers or other information/knowledge processing entities. SNA glossary follows:

Betweennes: The measurement of the node’s prominence according to its position in the network. Centrality: Measures who is central (powerful) or isolated in networks. Clique: A subgroup where actors are connected to each other as a maximal complete subgraph of three or more nodes (members) adjacent to each other. Closeness: The measurement of the distance between one node and other node in a network as the number of other nodes divided by the sum of all distances between the node and all others.

Cohesion: The representation of interactions’ weight (density), participants’ preferences (reciprocity), subgroups (cliques), and similar behaviour (structural equivalence). Density: The number of actual ties in a network compared to the total amount of ties that the network can theoretically support. Degree Centrality: A directed network where the direction of the communication is important.

Ego Network: Consists of a focal node and a set of alter nodes adjacent to or from the focal node. Equivalence: A description of the actors who have similar patterns of relations to others in the network and exhibit similar communication behaviour. Global centrality: The communication nodes between the members of a network characterised by direction and strength. In-degree centrality: The number of lines that are incident to a node. Intensity: The participation levels and persistence in online learning. Isolates: Nodes whose degree equals 0. Nodes: The actors or subjects of study. Out-degree Centrality: The number of lines that are incident from a node. Reciprocity: The number of ties that are involved in reciprocal relations relative to the total number of actual ties. Structural Equivalence: The role-set structure of a network based on the similarity of tie-profiles among its nodes and is computed by the Euclidean distance of tie-value from and to all other nodes.

Socio-Technical Design (STD): The design that is influenced by an organisations’ social structure. Thematic analysis: The process for encoding qualitative information in order to relate the data to prior ideas. Time-Short Series Design: A sequence of data points spaced and measured at short time intervals using methods to understand such time series, the underlying theory or to make forecasts. Usability: A quality attribute that assesses how easy user interfaces are to use. User-Centered Design (UCD): The design that considers the user into the center of software design. Vicarious Learning: It is the type of learning that occurs as a function of observing, retaining and replicating novel behavior executed by others.

Lambropoulos Phd Thesis 08

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PhD Thesis

Peter Lambropoulos · David Petrosyan Fundamentalsof ...