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Transcript of 6610johnstonmodule3a
A qualitative meta-analysis of social interaction in e-learning
Melanie Johnston
Meta-analysis methods
Step One: browsing of twenty Educational Technology journals
Step Two: identification of a theme
Step Three: conducted a search to find 15 studies related to the theme
Meta-analysis methods
Summary of studies selected
Years covered open-access journals 15 non-open access journals
1- 19993- 20021- 20031- 20041- 20051- 20062- 20073- 20082- 2009
11/15 4/15
Meta-analysis methods
Step Four: synthesized studies according to:o Purpose and Objectiveso Methods (Conceptual or theoretical framework,
education level, context, approach, participants, data collection, and data forms)
o Main Findingso Main Conclusionso Implications
Step Five: analyzed synthesis to determine any similarities, differences, and gaps
Meta-analysis findings
Meta-analysis findingsAuthor(s) Conceptual or theoretical framework
Godwin, Thorpe and Richardson (2008)
Fung (2004)
Sher (2008) Based on Moore’s extended framework; Social Learning Theory
Johnson (2007)
Lee and Rha (2009) Structure versus interaction
Insung, Seonghee, Cheolil and Junghoon (2002)
Cleveland and Garrison (2005) Community of Inquiry model
O’Reilly and Newton (2002)
Jeong (2009) Theory of dialogism
Yukselturk and Yildirim (2008)
Fahy (2002)
Rhode (2009) Interaction Equivalency Theorem
McIsaac and Vrasidas (1999) Symbolic interactionist framework
Fahy (2006)
Celentin (2007) Practical Inquiry model
Author (s) Surveys Interviews CMC text transcripts
Student ass’ts/ marks
# of participants
Godwin, Thorpe & Richardson (2008) * * 4 500
Fung (2004) * * 272
Sher (2008) * 208
Johnson (2007) * 127
Lee & Rha (2009) * * * * 123
Insung, Seonghee, Cheolil & Junghoon (2002)
* * * 120
Cleveland, & Garrison (2005) * 75
O’Reilly & Newton (2002) * 70
Jeong (2009) * 34
Yukselturk & Yildirim (2008) * * * 30
Fahy (2002) * 13
Rhode (2009) * 10
McIsaac & Vrasidas (1999) * * 8
Fahy (2006) * unknown
Celentin (2007) * unknown
Meta-analysis findings: methods
Data Collection and Participants
Author(s) Beliefs Perceptions Interview Transcripts
Survey Results
Discussion Transcripts
Ass’t Scores
Godwin, Thorpe & Richardson (2008)
* * *
Fung (2004) * * * *Sher (2008) * *Johnson (2007) *Lee & Rha (2009) * * * * *Insung, Seonghee, Cheolil &
Junghoon (2002)* * * *
Cleveland & Garrison (2005)
* * *
O’Reilly & Newton (2002) * *Jeong (2009) *Yukselturk & Yildirim (2008) * * * *
Fahy (2002) *Rhode (2009) * *McIsaac & Vrasidas (1999) * * *Fahy (2006) *Celentin (2007) *
Meta-analysis findings: methods Data Forms
Findings
Conclusion
Implications
Discussion
Conclusion
Implications
Study Reference
1 Lee, H.-J., & Rha, I. (2009). Influence of structure and interaction on student achievement and satisfaction in web-based distance learning. Educational Technology & Society, 12(4), 372–382.
2 O’Reilly, M., & Newton, D. (2002). Interaction online: Above and beyond requirements of assessment. Australian Journal of Educational Technology, 18(1), 57-70.
3 Fahy, P. (2002). Epistolary and expository interaction patterns in computer conference transcript. The Journal of Distance Education, 17(1), 20-35.
4 Fahy, P. (2006). Online and face-to-face group interaction processes compared using Bales’ Interactional Process Analysis (IPA). European Journal of Open, Distance and E-Learning,(1).
5 Yukselturk, E., & Yildirim, Z. (2008). Investigation of interaction, online support, course structure and flexibility as the contributing factors to students’ satisfaction in an online certificate program. Education Technology & Society, 11(4), 51-65.
6 Celentin, P. (2007). Online education: Analysis of interaction and knowledge building patterns among foreign language teachers. The Journal of Distance Education, 21(3), 39-58.
7 Johnson, E., (2007). Promoting learner-learner interactions through ecological assessments of the online learning environment. MERLOT Journals of Online Learning and Teaching, 3(2), 142 – 155.
Study Reference
8 Sher, A., (2008). Assessing and comparing interaction dynamics, student learning, and satisfaction within web-based online learning programs. MERLOT Journals of Online Learning and Teaching, 4(4), 446-458.
9 Fung, Y., (2004). Collaborative online learning: interaction patterns and limiting factors. Open Learning, 19(2), 135- 148.
10 McIsaac, M.S., & Vrasidas, C. (1999). Factors influencing interaction in an online course. The American Journal of Distance Education, 22-36.
11 Jeong, A., (2003). The sequential analysis of group interaction and critical thinking in online threaded discussions. The American Journal of Distance Education, 17(1), 25-43.
12 Rhode, J.F., (2009). Interaction equivalency in self-paced online learning environments: An exploration of learner preferences. International Review of Research in Open and Distance Learning, 10(1), 1-17.
13 Cleveland, M.-I., & Garrison, R., (2005). Facilitating cognitive presence in online learning: interaction is not enough. The American Journal of Distance Education,19(3), 133-148.
14 Insung, J., Seonghee, C., Cheolil, L., & Junghoon, L., (2002). Effects of different types of interaction on learning achievement, satisfaction and participation in web-based instruction. Innovations in Education & Teaching International, 39(2), 153-162.
15 Godwin, S.J., Thorpe, M.S., & Richardson, J.T.E., (2008). The impact of computer-mediated interaction on distance learning. British Journal of Educational Technology, 39(1), 52-70.