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TEACHING PORTFOLIO 2015: Professor Michael J Savage NATIONAL EXCELLENCE IN TEACHING AND LEARNING

NOMINATION Agrometeorology Discipline, School of Agricultural, Earth and Environmental

Sciences, College of Agriculture, Engineering and Science University of KwaZulu-Natal

Pietermaritzburg July 2015

Table of Contents Section Page

CV: Michael J Savage ....................................................................................................................... b

Table of Contents ............................................................................................................................... i

List of Appendices ............................................................................................................................ ii

The teaching portfolio statement ........................................................................................................ 1

1 Preamble ................................................................................................................................... 1

2 Philosophy/rationale for approach to teaching and learning: pedagogy to publication (thrust 1)

and community education in my area of expertise (thrust 2) ...................................................... 2

2.1 Philosophy........................................................................................................................... 2

2.2 Teaching and learning philosophy: a shared (open) web-based data and information system

for the agro-environmental sciences for teaching, mlearning and research ............................ 3

2.2.1 Literature review ........................................................................................................ 3

2.2.2 My philosophy and the AIM system: mlearning ......................................................... 4

2.2.3 Implementation of the AIM system ............................................................................ 5

2.2.4 The result ................................................................................................................... 5

2.2.5 Pedagogical description of AIM ................................................................................. 6

2.3 Educating the community in my field of expertise an essential part of the teaching and

mlearning philosophy (thrust 2) ........................................................................................... 7

2.4 Can technology fix education? A posting to a commentary .................................................. 7

3 Methods for teaching and mlearning, postgraduate supervision, research and innovation:

enabling postgraduates (thrust 3) and more than computer literacy (thrust 4) ............................. 8

3.1 The niche of the methodology of visual literacy and the fascination of near real-time ........... 8

3.2 Language stagnated role in teaching and learning and research .......................................... 9

3.3 Data sharing and group interaction using the AIM system .................................................. 10

3.4 Potential for use of the AIM system in schools ................................................................... 10

3.5 Postgraduate supervision methodology: participation in the AIM system and excellence in

postgraduate supervision (thrust 3) .................................................................................... 10

3.6 Innovative use of the AIM system for research................................................................... 11

3.7 Excel instruction: ensuring that students were more than computer literate (thrust 4) .......... 11

3.8 Limitations to my methodological approach to education ................................................... 11

4 Methods of assessing students work and performance ............................................................. 12

5 Evidence, impact and recognition of teaching and learning methods including AIM: Student

and peer evaluation, publicity and community engagement...................................................... 12

5.1 The result of the AIM system, including evaluation ........................................................... 12

5.2 Evidence: peer reports, student evaluations and awards ...................................................... 13

5.2.1 Videos and letters from past and current students ..................................................... 13

5.2.2 Peer evaluation of teaching....................................................................................... 13

5.2.3 AIM system evaluation using UKZN-approved questionnaires ................................. 13

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5.2.4 UKZN Quality Promotion and Assurance module evaluations using standard

questionnaires .......................................................................................................... 13

5.2.5 Excel instruction evaluation using a UKZN-approved questionnaire ......................... 13

5.2.6 Awards for research on teaching and learning ........................................................... 13

5.2.7 Descriptions of courses, modules or programmes developed ..................................... 14

5.3 Peer evaluation of teaching and learning through scholarship activities .............................. 14

5.3.1 Publication ............................................................................................................... 14

5.3.2 Conference and workshop participation .................................................................... 15

5.3.3 Unpublished materials .............................................................................................. 15

5.3.3.1 Dissertations based on the AIM system: completed and in progress/

preparation .................................................................................................. 15

5.3.3.2 Thesis/dissertation template postgraduate supervision ............................... 16

5.3.4 Videos, slides and other supplementary materials ..................................................... 16

5.3.5 Peer comment on contributions to curriculum development ...................................... 16

5.4 Recognition of excellence in teaching and learning ............................................................ 16

5.4.1 Recognition through invited seminars ....................................................................... 16

5.4.2 Peer recognition by UKZN: UTLO feature ............................................................... 16

5.5 Student success data .......................................................................................................... 17

5.6 Community engagement: educating the community in my field of expertise ....................... 17

5.6.1 Newspaper articles and other publicity ..................................................................... 17

5.6.2 Radio interviews ...................................................................................................... 17

5.6.3 Invited public addresses and collaboration with other institutions ............................. 17

5.6.4 Examples of use (selected) and evaluation of the AIM system by others ................... 17

5.7 Descriptions of educational research and innovation projects and funding granted.............. 18

6 References ............................................................................................................................... 18

7 Acknowledgements ................................................................................................................. 19

List of Appendices Appendix 1: Abstracts of published papers 20 Appendix 2: Newspaper articles on adverse weather 23 Appendix 3: Invited seminar/lecture 26 Appendix 4: Publicity on AIM 28 Appendix 5: Summary results of the open questionnaire on the AIM system 30 Appendix 6: Results of part of an open questionnaire used to gauge the role of the graphical

display of data in enabling further understanding of the agro-environmental concepts irrespective of language 33

Appendix 7: Excel lectures evaluation and questionnaire 34 Appendix 8: List of materials and (optional) supplementary materials 36 Appendix 9: Letters from past students 37 Appendix 10: Peer evaluation of teaching 39 Appendix 11: QPA evaluations (AMET210, AMET212, 2013 and ENVS318, 2014) 42 Appendix 12: UTLO feature: Scholarship of teaching and learning 45 Appendix 13: Student success data 48

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The teaching portfolio statement

1 Preamble My teaching and learning at the University of KwaZulu-Natal in agrometeorology, atmospheric science, bio-resources, irrigation science, philosophy of science and soil physics has spanned almost 40 years. My teaching now also encompasses research on teaching and learning which I regard as an essential component and continuous feedback mechanism for my teaching and learning philosophy and activities. I also did some teaching at Texas A&M University, Texas, USA on one of my sabbaticals and have experience in conducting postgraduate and in-service workshops in agro-environmental instrumentation across South Africa and neighbouring countries at Universities and weather services. During my career, I have been junior lecturer, lecturer, etc., to senior professor, the position I currently occupy.

My definition of agrometeorology is the study of the biophysical factors influencing the agro-environment so as to identify limiting factors but also so as to arrive at methodologies for improving agricultural efficiency. Agrometeorology also encompasses the study of the microclimate of humans and animals. On the one hand agrometeorology can be very theoretical but also applied. To some extent, it is easier to lecture a module that is predominantly conceptual and theoretical. However, it is much more challenging to lecture the same module with good participation and understanding, and to find applications of the conceptual and theoretical content that are relevant and understood by most learners.

Prior to 2010, agrometeorology and bio-resources class sizes were small fewer than 50. Over the last four and a half years, class sizes increased dramatically, exceeding 120 (first year), more than 175 for second year and 56 in third year (atmospheric science). During this period (mid-2011 to 2015) I introduced concepts in lectures using live data and used a web-based teaching, learning and research data and information system for the agro-environmental sciences using mobile learning. Many second-year agrometeorology students do the modules voluntarily with some doing them as compulsory modules. During this period I involved undergraduate students in research projects using live data based on a near real-time data and information system for the agricultural and environmental sciences the Agrometeorological Instrumentation Mast (AIM) system. These efforts with undergraduates resulted in seven publications and seven conference presentations, including one international paper (2015) and an international conference presentation (2012). And the students that register for my modules are not just science students they are agricultural, environmental and human science students.

These activities, the basis of thrust 1 pedagogy to publication (Sections 2.1 p2, Section 2.2.5 p6), involving under-graduates, live data and mobile learning, is unusual and innovative when I look at methodologies used at most tertiary institutions, even in other countries. It has an overhead staff time but is exciting, self-fulfilling and generates ideas for research and research on teaching and learning.

The second thrust 2 educating the community in my area of expertise (Sections 2.3 p7, Section 5.6 p16), focussed attention on the agro-environment and adverse weather but also on the AIM system.

The third thrust, through the development of Word templates for masters dissertations, PhD theses and long documents ensured that for thrust 3, postgraduates were enabled in structuring their writing (Section 3.5), understood the various elements of a dissertation/thesis and made use of the electronic templates and accompanying documents that explain the dissertation/thesis production process. The templates have been made available to many universities across South Africa and in Botswana.

In order to sustain this initiative, thrust 4 ensured that students were more than computer literate (Section 3.6 p10), and capable of manipulating and interrogating large datasets using Excel.

These four thrusts, which overarch my teaching and learning philosophy, ensured that there is a continuum of activity from undergraduate to postgraduate studies through to community engagement. These activities are not only about agrometeorology. It is more than that, including many disciplines.

The description of my philosophy on teaching and learning and associated research described here focuses mainly on activities over the last four and a half years. The background to these efforts is also discussed. Also described is the use and role of live data for undergraduate teaching and learning and associated research and publication activities, and the role of language, including use of such data by postgraduates, staff and other researchers in their research. At the appropriate stages, we have interacted with various stakeholders about the use and improvements of the system developed.

A softcopy of the documentation, two videos and supplementary materials are available at: https://www.dropbox.com/sh/4iipodz3uhpys6v/AAAueojR0OvIw4uY3slSqkqAa?dl=0

https://www.dropbox.com/sh/4iipodz3uhpys6v/AAAueojR0OvIw4uY3slSqkqAa?dl=0

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2 Philosophy/rationale for approach to teaching and learning: pedagogy to publication (thrust 1) and community education in my area of expertise (thrust 2)

2.1 Philosophy Agrometeorology is a difficult subject. It applies to the agro-environment. Introductory subject matter includes concepts such as radiation, energy in various forms, radiation and energy balances, wind and advection, evaporation, and application of these concepts to remote sensing, frost, El Nio, climate change, photosynthetically active radiation and micrometeorology, for example.

Three problems: many of the concepts are invisible. Usually, we cannot see directly evaporation, infrared radiation, greenhouse gases, wind other than its effects, atmospheric pressure, etc. Secondly, many of the English technological terms that are used in the agrometeorology modules do not exist in the home language of the student. Thirdly, the students are from academically diverse backgrounds from a wide range of degree programmes and disciplines.

So then, how does one teach, get students to learn, research and think about this difficult agro-environmental subject matter, which involves invisible things, to students who do not have a language of technological terms used in the description of the subject and also to such academically diverse students? Even at the second year level, most of the students have never met agrometeorology in their lives before. And, the students interest may range from human sciences to agricultural plant sciences, chemistry, geography, ecology, grassland science, hydrology, soil science . Surely this is an impossible task? I thought that about a decade ago but have now a changed mind.

Prior to 2010, I had not considered the possibility or realised the potential or importance of the research aspects of teaching and learning in my field. Over several decades prior to 2010, I had focused on research and university administration in spite of having a heavy teaching load in excess of 14 lectures per week for sixteen years. For me, teaching was just a job function but not a focus for research. Research on teaching and learning was not possible, I thought. Partly, this was due to the over-emphasis of the University on (traditional) research and publication as a requirement for personal promotion. Also, due to the promotion model, I was much more driven and interested in research. I did not view teaching and learning as having the potential for research. Prior to the 2010s, my teaching, learning and research philosophy had been that at the first and second year levels, it was not really possible or necessary nor even desirable to mix teaching and learning with research. Research was kept as a separate entity that undergraduates could not grasp nor one in which they could participate. My own current research was not even discussed in lectures students had to have a rite of passage to this over three or four years and then it only involved students that excelled. The only exposure by students to my research was when I took them outside to our agrometeorological station.

In the 2010s, that exposure changed with changes in technology and information systems becoming available and usable in the lecture room/laboratory using for example networks and Wi-Fi. I then realised that it was possible to bring live agro-environmental data and information into the classroom bringing the outside inside and making the invisible visible. In the 2010s, there were also major improvements in sensors, datalogger sophistication, data telecommunication methodology, information systems, computer software, computer capability and device storage capacity. Also, class sizes were increasing with more students with diverse academic backgrounds, and language, without concomitant increase in equipment, laboratory space, technical support and demonstrator budget allocations.

My educational philosophy now is that teaching and learning, including research on teaching and learning, involves my understanding the problems that students have in understanding the subject matter of agrometeorology. An empathetic approach. I would get angry with myself when I saw that they did not understand certain key concepts. This inward anger, which I regarded as a failure, would drive me to find a more visual approach to enlighten their understanding. Overarching my philosophy specifically on teaching and learning are the four thrusts mentioned in the Preamble, which stem from my philosophy. My philosophy is fourfold.

First and foremost, from a teaching perspective, my philosophy to teaching and learning entails understanding the students learning difficulties but at the same time reminding them of their everyday experiences of the agro-environment while developing the basic concepts revealing the unseen.

Secondly, my philosophy has been one of engaging directly with the students, especially during the lectures and practicals and small-group sessions, about what they know, have been taught and have learned, again making use of everyday agro-environmental experiences. Even in large second-year

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classes more than 175 this would involve walking around even to the back of the class to ask questions to encourage thinking and elicit responses. Continual and animated engagement. This engagement includes trying to relate complex subject matter in a way that allows easier understanding by students. Important also is the continual reliance on visual teaching materials in various forms including visual displays of the current outside environment inside the lecture room. Using a combination of empathy, continual animated engagement to encourage thinking and reliance on visual teaching material results in it not being a case of me trying to get the student to my level but of me getting to their level. At the same time, I try hard to impart knowledge gained by both students and myself in a way that they can more easily relate to. This effort also included making lecture material, through use of PowerPoint, the Internet and other aids, as animated as possible. My experience, years earlier, with the use of PowerPoint animation in lectures was invaluable in developing the AIM web-based teaching, learning and research system described later. Using humour is also an essential part of my teaching and learning philosophy and assisted in engaging confidently with students, developing important concepts and improving the student knowledge base. At the same time, an open and friendly relationship with students was developed very quickly.

Thirdly, my teaching and learning philosophy is that once there has been sufficient knowledge (teaching) and skills transfer (learning) to the students, their knowledge and skill has to be applied (research) as soon as possible through the practicals and the student (group) projects using (thrust 1) from pedagogy to publication. I regard this application as an essential part of the overall teaching and learning (and research) process, including getting students to think, even though this significantly increased my workload. Workload increased for class sizes in excess of 50 since all class projects are different, under-resourced (human and equipment resources) and need careful planning in terms of data availability, equipment, and laboratory space, relevance of project to each student in the group, demonstrator knowledge and their availability and also staff availability. The group projects are typically 25 in number in a semester each with typically six members depending on class size, including a group-elected convener. The projects are usually related to their choice of major and project relevance. Students then work in their groups for all activities practicals, research and discussions. I had tried this previously with smaller classes and it was successful. Most of the research projects had to involve or be related to near real-time data and information accessible anytime and anywhere mobile learning. The projects, using demonstration of concepts were also intended to result in publications and conference presentations: pedagogy to publication. Therefore, the teaching and learning process is very much based on agro-environmental applications and research of what has been learnt by the students. Making use of live data and graphics piqued student interest but I initially (2011) did not understand fully the mechanisms for the success of linking live data to lectures, practicals and projects nor fully appreciate its potential for research, in teaching and learning and for use by postgraduates and staff.

Fourthly, I make undergraduate projects link to postgraduate/staff research and vice versa with an emphasis on data and graphic examination anytime in different places using various technologies, even using the students cellphone. In cases where that link did not exist, undergraduate projects that had the potential to be expanded to postgraduate research topics were offered to new postgraduates or used for staff research. And, postgraduate projects were used to spawn undergraduate projects.

Heres the thing: I no longer see undergraduate teaching and learning as separate activities from research activities. There is no longer a rite to passage all students deserve the right to be involved in the research even in second year. Moreover, the research needs to involve contemporary agro-environmental topics and focussed on the research on the teaching and learning approaches/ methodologies.

2.2 Teaching and learning philosophy: a shared (open) web-based data and information system

for the agro-environmental sciences for teaching, mlearning and research1

2.2.1 Literature review Agrometeorology and many agro-environmental disciplines, as applied technological disciplines, are initially challenging to undergraduate students and even postgraduate students. In the case of agrometeorology, many of the students have a first language for which the words "meteorology" and

1 Based on Savage (2014b) and Savage et al. (2014), both of which emanated from undergraduate student projects

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"agrometeorology" do not exist. Also, the teaching, learning and research of agrometeorology presents significant challenges due to the use of mathematics, physics, meteorology and technology in agricultural and environmental applications and the many invisible concepts.

Climate change is upon us and yet many students have a poor conception of it, its consequences, and of their environment, poor numeracy ability, poor interpretation of the graphical display of data and limited ability of statistically manipulating agro-environmental data. Often this poor conception is due to a lack of exposure to such data, and their visual display, associated with important elements making up the environment. My experience, over many years at many different institutions both locally and internationally, has been that students are not adequately exposed to information and data that directly reflects the state of the environment around them and they may therefore leave university with a degree that has not sufficiently equipped them with a first-hand understanding of the agro-environment. They are therefore unable to easily relate to the problems of our uncertain agricultural and environmental future. Students often lack a basic understanding of important agro-environmental concepts such as temperature (for example, air temperature, temperature gradient, temperature scales, rate of change of temperature) and more complex concepts such as solar irradiance, surface radiation balance, and the graphical display of information in various forms. Often students have difficulty in "reading" graphs (Lowe 2000, Aoyama and Stephens 2003, Aoyama 2006), and the difference between a temporal graph and a regression graph, for example, is not appreciated. These deficiencies are evident when students start to collect agro-environmental data for their practicals and projects or are assigned tutorials not just for their modules in agrometeorology but for most of their other modules as well. Also relevant and pertinent to South African students, is the question: does the use of graphics and data in teaching and learning transcend language differences between students and between student and staff, more than does written text and other resources (Savage 2014b, Savage et al. 2014)?

Lowe (2000) and Felten (2008) use the term "visual literacy", stating that it is an essential component of science and technology education. Arcavi (2003) refers to this lack of interpretation of data as "seeing the unseen in data" and that " seeing, with the aid of technology may also sharpen our understanding, or serve as a springboard for questions which we were not able to formulate before". Using observationally based climatic data sets and focusing on the (possible) cause(s) of global warming, Schweizer and Kelly (2005) found that students used observationally-based climatic data sets supplied in a variety of ways such as "(for) supporting their own argument; negating the argument of the opposing side; presenting challenges to the opposing side; and raising new scientific questions".

2.2.2 My philosophy and the AIM system: mlearning My philosophy and efforts have been to attempt to link agro-environmental conceptual material for a range of disciplines to measurement systems and in turn to collected data. This includes the display of such data, in graphs, tables and icons, and other information that are easily accessible at any time or place to undergraduate and postgraduate students and staff even in the lecture room mobile learning (mlearning). The implemented system emphasises "seeing live data", "visual literacy" and "seeing the unseen" through their display and interweaving computer literacy, mathematical manipulation and basic statistical manipulation of near real-time agricultural, earth and environmental sciences data and information. However, it needs to be more than just seeing live data it needs to be changing data that reveals events in a dynamic fashion, such as in a graph that reveals events changing in time or space and the graph and data need to be easily accessible to the students, staff and demonstrators. So as to capture the attention of the students, it should not just be data but revealed data depicting adverse weather events such as Berg winds, coastal low pressure systems, extreme heat including human comfort, frost, storms, etc. all of which the students may experience in any given semester and which captures their attention. Through its emphasis on visual literacy, including mlearning, the system has enabled deeper understanding of biophysical agro-environmental concepts, irrespective of language.

Discussing the next decade of environmental science in South Africa, Shackleton et al. (2011) state: "new graduates will be ill-equipped to deal with the new environmental challenges and thinking as they emerge, and research programmes will be unable to contribute to meaningful knowledge frontiers or solutions. This places a particular responsibility on universities to adopt a dynamic approach to teaching (and mlearning!) and research around environmental science, as well as the need for frequent stock taking and alignment of environmental science programmes with the latest developments internationally." The interdisciplinary near real-time teaching, mlearning and research web-based Agrometeorological Instrumentation Mast (AIM) data and information system that I have developed

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over several years http://agromet.ukzn.ac.za:5355 is largely based on agrometeorological and agro-environmental applications and is pillared on the approach of "a dynamic approach to teaching and research" relevant to a range of disciplines. These philosophies and approaches are also in keeping with the recent Council for Higher Education (2013) report that "The conditions on the ground dictate a fundamental systemic review of the undergraduate curriculum".

2.2.3 Implementation of the AIM system One way in which the AIM system is introduced to the students is through their first practical that includes a scavenger hunt. Students are asked agro-environmental questions that then require them to visit the AIM site and interrogate the AIM system screens for the answers. As and when topics arise in lectures, or adverse weather occurs, the AIM system and its live data are shown. They also visit the AIM system site as part of three practicals and their projects. More than half of their practical work involve use of the AIM system. For the practicals for example, they collect their own data and compare their data with that collected by the AIM system. For their projects, they visit the site to view and service the equipment that is used for the data collection of their project.

While the AIM system has been developed for the agro-environmental sciences, the work could also be used as a case study to extrapolate broad principles that may be applied to mlearning in other disciplines. Staff in other disciplines that have made use of the system include staff from agricultural engineering, agricultural plant sciences, ecology, geography, grassland science, hydrology and soil science, and it is used by undergraduates, honours, masters and PhD students in agrometeorology and other disciplines and schools. It is also used by a number of research groups that do field research close to the AIM site the CSIR and the Institute for Commercial Forestry Research, for example. The AIM system is now used regularly by undergraduates, postgraduates and staff. There is also the potential for mlearning use in junior and high schools, but there is a lack of postgraduates to investigate this aspect. This year, two undergraduate projects explored implementation of the AIM system in high schools one project group investigated use in a grade 10 class and another use in a grade 7 class. A screen was created specifically for their use with extensive use made of images to depict agro-environmental events. The AIM system has also provided an avenue for research in a number of areas not previously pursued it is the basis of three papers in preparation, two for international journals!

2.2.4 The result The AIM system, developed over the last four years has become a shared resource within the College of Agriculture, Engineering and Science. It has resulted in several peer-reviewed publications (Appendix 1 p20-22) based on undergraduate student projects. I fully describe the AIM system in a paper (Savage et al. 2014, Appendix 1 p20 bottom), in a dissertation (Savage 2014b), and apply it in another five papers and in two peer-reviewed conference papers (Appendix 1 p22). Other conference presentations, including one international (Savage 2012, p15), applied or further described the system (conference presentation, p15). All publications made extensive use of the AIM system (Savage 2012a, 2012b, Savage 2014a). The fifth paper, on nowcasting the daily minimum temperature (Savage 2015), has been published in one of the top international journals in my field International Journal of Biometeorology (Appendix 1 p20 top). This paper was based on research I did with second year undergraduates in 2011. The Savage (2012a) paper on frost (Appendix 1 p21 top) was judged at national level as the best paper published in 2012 by the Editorial Board of the South African Journal of Plant and Soil. A conference presentation of mine that was based on the AIM system (p15) and presented at the 2013 Combined Congress (Crop Production, Soil Science, Horticulture, Weed Science), was awarded the best presentation award out of 230 entries at a national conference. Apart from Savage (2014a), all of the published papers based on the AIM system started off as second-year student projects. These outcomes have redefined my teaching, mlearning and research philosophy, and the methods used for the teaching of agrometeorology at undergraduate level at UKZN, and has redefined the approach I have used for undergraduate and honours projects, postgraduate studies and even my own research. These outcomes have also excited the undergraduates at all levels, and postgraduates, and demonstrated what is possible.

The AIM system has proved to be a useful and contemporary, shared, visual, and data and information resource for teaching and mlearning for undergraduate and honours students (three) and has also become a very useful research tool for postgraduates (six) including two PhD students, and staff (seven). Researchers at other overseas universities have also made use of data provided by the system: Oregon State University in the USA and the Technical University of Delft in the Netherlands.

http://agromet.ukzn.ac.za:5355/

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The AIM system has also been used and evaluated through the use of questionnaires by UKZN students2 and, for the last two years, by physics students from the University of Botswana. Although mainly for undergraduates, increasingly postgraduates have used the system (2014: four masters and two PhD students that I supervise) with postgraduate and staff research feeding into undergraduate teaching, practicals and projects through near real-time display of data and information. Two completed masters dissertations (both cum laude), two masters dissertations being finalised, two current masters and two PhD projects initiated have used the AIM system or have extended it. The AIM system has also been used by three honours students for their honours projects, two graduating cum laude.

2.2.5 Pedagogical description of AIM A pedagogical description of the UKZN AIM system is depicted in Figure 1. The various interacting components such as the ENVIRONMENT, the NEAR REAL-TIME DATA, TEACHING, STUDENT, etc. are shown. There is however, a missing component. Can you spot it? From the perspective of the ENVIRONMENT, NEAR REAL-TIME DATA are generated and stored on-site by the AIM SYSTEM which then data-telecommunicates with the server. The software that is continuously running on the server then updates the prescripted icons, tables, figures that visually represent the data (VISUAL LITERACY). The STUDENT through directed TEACHING then accesses the information, seeing the data and graphic information with little reliance on language. This would be a traditional way of explaining AIM system functioning. The traditional explanation usually fails to emphasise the link between the STUDENT and ENQUIRY. In lectures, practicals or in their research projects, particular agro-environmental events through TEACHING may be discussed/highlighted. For example, rainfall intensity, high solar irradiance, Berg winds, fire danger, floods, human comfort. This TEACHING may result in the STUDENT making an independent ENQUIRY of the system using their cell phone, tablet, and laptop or LAN/laboratory computer. The STUDENT may have experienced windy conditions, hot conditions, or cold conditions, of the ENVIRONMENT, etc. on the way to or from lectures. The STUDENT ENQUIRY then sets up a chain reaction of events culminating again in a visual display of data and graphic information with little reliance on language. Once the student has done this a number of times, they are hooked! Evidence for this is the surprisingly high percentage of respondents indicating personal use of the system. From a teaching and mlearning standpoint, this has

2 All questionnaires used for evaluating AIM system (2013-5) use have formal approval from the UKZN

Humanities and Social Sciences Research Ethics Committee (protocol reference number HSS/0549/013,

HSS/0549/014 with the University of Botswana added as an additional site in 2014)

AIM system

Visual literacy

LanguageEnvironment

Near real-time data

Student

EnquiryTeaching

Figure 1 Pedagogical description of the application of the UKZN web-based AIM system for teaching, mlearning and research, excluding the missing element. Dashed lines indicate mlearning

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benefit for the undergraduate student since personal use is the one usage that would probably continue even after the student has completed the current module or year of study. Mlearning and its role in the AIM system needs to be harnessed further, including use with social media such as Facebook, Twitter, WhatsApp, etc., possibly including the role of language.

As pointed out by Savage et al. (2014), available on request, in a description of the AIM system as an innovative research tool, "The continual and automatic graphical display of research data allows for a dynamic and visual interrogation of measurements which can assist in developing ideas for more detailed displays or developing further ideas". While the STUDENT is mlearning through an ENQUIRY using the AIM system, they are also DOING RESEARCH the missing element of Figure 1. This is the key: the integration of mlearning and research processes with lectures providing directed teaching. The mlearning processes between the various elements of Figure 1, viz., STUDENT, ENQUIRY and ENVIRONMENT are shown by the dashed lines. Some of the arrows in Figure 1 are double-arrows, implying, for example that an environmental event or change in the environmental conditions may result in a student enquiry, i.e. research, or that the student may decide to enquire through the teaching process.

The link between (thrust 1) pedagogy and research is clear in Figure 1. What is also not shown though is the intention of publication through research projects with students, postgraduates and other staff using the mlearning and ideas emanating from the display of live data.

We have attempted to reveal the secrets of live data in a multilingual setting, promoted interaction between different users of the common set of live data, and early identified problems with live data. Our effort reflects integrating teaching and research in a uniquely engaging student-focussed way and through linking undergraduate projects to postgraduate research and vice versa.

2.3 Educating the community in my field of expertise an essential part of the teaching and

mlearning philosophy (thrust 2) My philosophy to education has also been to highlight the role of the AIM system, agrometeorology and the agro-environment, to the community through articles on adverse weather in newspapers (Appendix 2 p23-25), invited public addresses (four) (Appendix 3 p26-27) and radio media (one local and twice nationally) and publicity (Appendix 4 p28-29). I see these efforts as engaging with the community and at the same time (thrust 2) educating the community in my field of expertise. These attempts focussed attention on the agro-environment and adverse weather but also on the AIM system. It is the mandate of national weather services to alert the community to adverse weather. The open AIM system also communicates this well through display of near real-time data and information and educates, enabling community mlearning. Students realise that these communications to the community play a role and alert them to roles they may play once they have graduated.

2.4 Can technology fix education? A posting to a commentary The extract below is taken from my posted comment, quoted below, in The Chronicle of Higher Education (http://chronicle.com/article/Why-Technology-Will-Never-Fix/230185/) to the commentary "Why technology will never fix education" by Toyama (2015): "I agree that it is best never (to) say never... Title of commentary is "Why Technology Will Never Fix Education". I do not fully agree with the sentiment that technology will never fix education. It depends on many factors. It depends on how it is used, for what purpose and for what environment - and other factors, particularly "buy-in" by staff.

Maybe technology will not fix all of education but certainly it can fix parts. Or at least that has been our experience.

We have found technology to assist in the teaching (of) multi-cultural and multi-lingual introductory classes for courses in the agro-environmental sciences. But also to assist in the projects that we give to the students. It is through their projects that the technology makes a major impact.

We display live weather data to students in a lecture room and laboratory and they use the data for their projects. The data are displayed in a web-based system in graphs and icons and made available for downloading. Classes are at second year University level and students range from the agricultural sciences to humanities to applied sciences. Usually, we cannot see directly evaporation, infrared radiation, greenhouse gases, wind other than its effects, atmospheric pressure, etc. How does one

http://chronicle.com/article/Why-Technology-Will-Never-Fix/230185/

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display the invisible other than using technology for the measurements? And then technology is required to display the invisible in the lecture room.

In questionnaires, more than 80 % of students said that they benefited from system use, that their appreciation of ranges of the various weather elements had improved, that system use had improved their ability to manipulate data in a spreadsheet and/or display data in graphic or table form, improved their appreciation/awareness of global climate change and/or global warming aspects and that system use had improved their appreciation/awareness of the graphical display, and trends, of agro-environmental and environmental data.

With the use of technology, we have found that the use of graphics and data in teaching and learning transcends language differences between students and between student and staff, more than does written text and other resources."

3 Methods for teaching and mlearning, postgraduate supervision, research and innovation: enabling postgraduates (thrust 3) and more than computer literacy (thrust 4)

3.1 The niche of the methodology of visual literacy and the fascination of near real-time

The students I am exposed to have an innate desire to know more, see more and even experience more about the agro-environment. Therefore, to bring the outside environment inside a depiction of the outside agro-environmental conditions in the lecture room, in the laboratory, on their cell phone, PC, laptop, tablet via Wi-Fi, SIM card connectivity or LAN cable has always been an interest of mine and is something that is fascinating to many students. And not only to students even to my wife!

Making mlearning (and teaching) more visible, and also visual literacy, has been something I have wanted to do decades ago using live data available all the time at any place. The technology for what I wanted to do did not exist then, so I used to take the students to a weather station to show them the instruments used. The learning process took place outside. However, I could not show them the data not then anyway. And in fact not even a week later or at least not until the display of data on a pen-chart recorder had been transcribed and typed into a computer. By then they had lost interest. We then decided to write the previous days maximum and current minimum air temperature and accumulated monthly rainfall on a blackboard in the foyer of a building for all to see. This was the seed of mobile learning and visual literacy for agrometeorology in the early 1980s. Technology changed the way we collected and stored data fast microprocessors, high capacity hard drives and electronic sensors became available and were cheaper. These technologies allowed data to be collected automatically and stored in datalogger memory. Nevertheless, an important learning site of the 1990s, the outside, was still outside and had to be visited to view or collect data. Subsequently, data telecommunication, through the cell phone, Internet, landline, radio, satellite, or Wi-Fi technologies transformed the thinking on how data were telecommunicated, stored and displayed possibly enabling mlearning. Tertiary institutions were however very slow, even today, to take advantage of such technologies for pedagogical purposes and not only in the agro-environmental sciences. Data telecommunication is only one part of a chain of events though. In isolation, it is simply a method of collecting and storing the record of data. It does not however reveal the secrets of the data, nor does it promote interaction between different users of a common set of data, nor allow early identification of problems with the data, if any.

Data telecommunication in the 2000s needed to be taken further viz., data needed to be accessed, manipulated and displayed almost as soon as it was collected to: reveal its secrets, reveal some aspect of the agro-environment, reveal some possible problem with the data and enable mlearning before it could be a pointer to further understand the agro-environment, or to rectify the measurement problem or to reveal "what to do from here" by one or more users of the data system. This required the use of the Internet as well as user-friendly (and powerful) software that became available in the late 1990s. The communication surrounding the data is between not only users of the data but also between users and the very data! User(s) can independently intervene at any time to display data differently with others then commenting on the result(s). This dynamic intervention by one or more of the student research group (and staff) with the near real-time display of data and information results in changes in thinking and understanding quickly and more so than other methods used previously. Dynamic visual literacy on demand? Mlearning and visual literacy? It is visual literacy, but it reveals and sometimes in a dramatic fashion. Witness the awe, and excitement, of the students (and demonstrators and staff!) in the laboratory during a summer storm, seeing the amount of recorded rainfall displayed in a graph on the

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AIM system and at the same time seeing evidence of it in the ever increasing soil water content as it approaches the saturation water content and the dreaded flood event.

The AIM system has over the last four and a half years totally redefined my educational teaching and learning philosophy and the way my modules are taught. Besides promotion of mlearning, one of the most powerful aspects of the innovation of the AIM system is its applicability to a wide range of disciplines. The system allows lecture material to be directly accessed using near real-time events and historical data relevant to many disciplines: agricultural engineering, agricultural plant sciences (crop science, horticultural science, and plant pathology), agrometeorology, biological sciences (ecology), environmental sciences, geography, geology, hydrology, irrigation science, soil science and others. The product is a field-based, meteorological, agricultural and environmental sciences system linked via radio telecommunication to a laboratory computer connected to the Internet with regular uploads of data in table form and graphics bringing the outside environment to the inside at any time or place. Pre-programmed alerts to interested students, based on near real-time measurements and calculations, are in various forms including SMS, emails, FTP (File Transfer Protocol) or indicator buttons displayed by the graphical uploads to the Internet. The nature and implementation of the AIM system and the content of the undergraduate student projects instils an inter-disciplinary culture of research to students.

3.2 Language stagnated role in teaching and learning and research

Historically in South Africa, separate development meant poor communities received separated education and were not exposed to changing information, technologies and advances, and did not keep up with current happenings in a changing world. Lack of access to information and changing technologies meant that advancement, changes and additions to language probably did not occur with the result that many new concepts that appeared in English and Afrikaans dictionaries, for example, did not appear in isiZulu and other dictionaries. Generations of people, were not only deprived of technologies but were also isolated from the global village and their language stagnated. Language stagnation exists even today and is a major problem to pedagogy. [To some extent this is still happening today with many unable to access the Internet from an educational standpoint due to technological challenges and cost of technology including the relatively high cost of bandwidth in South Africa.] Language stagnation needs to be fixed, urgently. For example, while there is an isiZulu word for "dew", there is no isiZulu word for "dew point" (de Schryver 2010). Our research, through the use of four questionnaires, has shown that for the future, there is an urgent need to create a list of isiZulu technical terms specific to agrometeorology and allied disciplines. I have started this with the assistance of undergraduate students (AMET210 and AMET212 projects, 2014 and 2015). In addition, since the method of AIM encourages understanding of concepts via the graphical display of data, the role of language is diminished. I need a postgraduate student interested in science education, and the role of language, to investigate this aspect. This demonstrates possible use of the AIM system in the future.

Explored to some extent in the work and methodology on the AIM system, and pertinent to South African students and based on personal experience, is that use of graphics and data in teaching and mlearning may transcend language differences between students and between students and staff, more than written text and other resources (Savage 2014b, Savage et al., 2014). In the use of the AIM system, it was assumed that graphical and table displays of data reduced the role of language and assisted in cognitive retention of information. In a second questionnaire (Appendix 5, p30-32), respondents indicated that the graphical display of data and information had enabled further understanding of agro-environmental concepts irrespective of language (89 % for the 2013 questionnaire (Appendix 5 p32, Question 17) and 76 % for 2014 (third) questionnaire (Appendix 6 p33)). The role of language, visual literacy and use of the AIM system deserves further attention in the future as transdisciplinary research projects. The third questionnaire showed that students that did not have English as their mother tongue did not mind having lectures in English! mainly since technological terms used do not exist in their language.

All technical terms used in AMET210 for which there is no isiZulu equivalent have been entered into a spreadsheet. As part of one of the projects, a group of students proposed isiZulu terms and the spreadsheet was then updated annually since 2013 and made available to all students. I have formally approached two scientific societies (South African Society for Atmospheric Sciences and South African Society of Crop Production) with a proposal that a Joint Society Steering Committee create a technical glossary of terms for isiZulu and isiXhosa for the Atmospheric Sciences be established. The most current version of the spreadsheet list of terms is available on request (or available as part of the

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supplementary materials: https://www.dropbox.com/sh/4iipodz3uhpys6v/AAAueojR0OvIw4uY3slSqkqAa?dl=0

3.3 Data sharing and group interaction using the AIM system

Pursued to some extent in the study was the role of the system as a near real-time system for arriving at visual comparisons of raw and/or analysed research data, according to a pre-defined template, on demand. Regression and/or temporal graphs, based on fuzzy logic expressions, were updated regularly and shared online by group members. Following agreement by all group members, a member could alter the fuzzy logic expressions, and hence the visual displays. I tried this for Berg winds http://agromet.ukzn.ac.za:5355/?command=RTMC&screen=Berg%20winds and it worked quite well. Individual research group members could tweak the underlining code used, allowing a form of fuzzy-logic to be used to replot the near real-time graphs. The members therefore do not need access to the actual measurement data. Through the graphical display or the display of an agro-environmental event and outcome-based calculations, which could be in time and space, the members develop the thinking behind what to do with the measurements. What is this? A sort of user-driven meta-data analysis and mlearning? This research was the subject of an MSc (cum laude, 2015) that I supervised. In another example on different methods for measuring air temperature (Savage 2013) and another on the microclimate in a car, an AIM system display was used to make decisions in real time on the adequacy of methods, compared to standard methods, and methodological changes made. In both examples, this resulted in timely decisions and reduced effort in arriving at best measurement methods.

I think we have just touched the tip of an iceberg! There is so much more that could be done. Quite a long way from reading thermohygrographs from the agrometeorology site and sharing the data by writing it on a blackboard in the foyer of a building!

3.4 Potential for use of the AIM system in schools

As mentioned previously, another area for future research is the application of the AIM system to high and junior schools. It is envisaged that a screen describing and displaying the weather elements be designed and then used by school learners. In this regard, the role of visual literacy in teaching and learning needs further research. The visual reinforcement of measurements and measurement ranges could allow the Web-based AIM system to be used in a junior and/or high school. Through the use of simple images based on a combination of near real-time measurements, the complexity of the agro-environment could be made much simpler through the use of data or data combinations shown as simple visuals including graphics associated with near real-time events (http://agromet.ukzn.ac.za:5355/?command=RTMC&screen=Human%20comfort).

An image of a physically active person could be prescripted to change depending on the near real-time environmental conditions an active person would appear when conditions safe to do active events prevailed. When conditions are adverse, a person with shade and sunscreen and drinking water then appears. Arrows on this screen move to indicate numeric values describing the prevailing conditions. These mlearning graphical reinforcements would allow the system to be used in a multi-language environment. The equipment required for use of the AIM system in a school environment would be a web-enabled computer and if necessary, a data projector. This year, two undergraduate project groups will investigate the use of the AIM system in schools.

3.5 Postgraduate supervision methodology: participation in the AIM system and excellence in

postgraduate supervision (thrust 3)

The methodology used in the AIM system project is student-centred. Two post-doctoral students and a PhD student assisted me in its physical establishment. The AIM system has grown due to participation of the undergraduate and honours students, postgraduates and staff that have made use of it.

Supervision and excellence in research is part of the teaching and mlearning thrust and directly links to it. Examples include the fact that for four consecutive years (2012-5), a cum laude masters has been awarded to an agrometeorology student. My postgraduate supervision load is very high (currently one honours student, seven masters and seven PhD students and two external PhD students (University of Bern, Switzerland and Agrocampus Ouest, France)).

As part of teaching and mlearning, in an effort to prepare postgraduates for dissertation/thesis production, thrust 3 focussed on enabling postgraduates to structure their writing. For this purpose, I

https://www.dropbox.com/sh/4iipodz3uhpys6v/AAAueojR0OvIw4uY3slSqkqAa?dl=0http://agromet.ukzn.ac.za:5355/?command=RTMC&screen=Berg%20windshttp://agromet.ukzn.ac.za:5355/?command=RTMC&screen=Human%20comfort

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developed Word templates for use by postgraduates but also for the preparation of long documents available as supplementary materials: https://www.dropbox.com/sh/4iipodz3uhpys6v/AAAueojR0OvIw4uY3slSqkqAa?dl=0 The Research Committee of my School has approved this.

I have always encouraged my postgraduates to attend and participate at conferences. Even honours students (for example, Strydom and Savage 2013). He obtained his honours cum laude for this research. Based on masters research, one of my students who I supervised won first prize in the poster category at a national conference on Global Change in Boksburg. Last year, for his PhD research that I also supervise, he won the top award at the research day for the best oral presentation in the UKZN College of Agriculture, Engineering and Science. The award included a funded overseas conference visit. He presented a poster that I co-authored.

3.6 Innovative use of the AIM system for research A near real-time energy balance system, and an AIM screen devoted to this has been established. The system uses the surface renewal approach, implemented in real-time, for the determination of sensible heat flux from which evaporation is determined and displayed using the AIM system. The system is used for research but also for teaching and learning at all levels including use by postgraduates. The methodology of the approach is described by Savage (2014b). A provisional patent has been applied for by UKZN (PA149514PCT and international application number PCT/IB/ 10/53946) with the project now funded by the Technology Innovation Agency (of the Department of Science and Technology).

3.7 Excel instruction: ensuring that students were more than computer literate (thrust 4) When we first implemented the AIM system, we soon noticed that students were not capable of handling large datasets and were not able to interrogate data. We needed them to be (thrust 4) more than computer literate. We replaced three traditional practicals with instruction on graph plotting and six hours of instruction using Excel. The emphasis was on graph plotting and data handling. We monitored their progress following this intervention using formally-approved UKZN questionnaires and motivated for similar interventions (supplementary instruction) elsewhere in the School. These suggestions were accepted by the School and acted on in 2015, affecting hundreds of 2nd-year students.

3.8 Limitations to my methodological approach to education

However, there are still many obstacles, not the least being infrastructural support. I can only hope that in time these challenges can be overcome: lack of laboratory space, lack of computers, lack of equipment and aging equipment, lack of support staff, and many problems with the administration of finance and supplies and equipment acquisition, etc. I fear however that this may take too long unless urgent measures are put in place, including infrastructural improvement, to assist us with the ideas I have for the improvement of all students. Of particular note, I have noted a sense of, and seen, frustration by students in being unable to master key skills that they know hinder them from a greater understanding of the agro-environment. That frustration goads me in the realisation of the urgency of the matter. It will be a case of which one wins action or frustration! When I see students master these skills, there is joy and a great sense of empowerment by the student, breaking the shackles of utter frustration.

The system also suffers from technological challenges that we need to solve. There are frequent disconnects to the WebServer (commercial) software. Initially, these were not that frequent but they are now more frequent sometimes as many as three each day. The disconnects necessitate a manual reset of the WebServer software, even over weekends. The system has grown to the extent that its various screens need to be separated into public for general use including use in schools and others for research. The expansion of the AIM system, which involves expansion from one to three servers, now has the support of ITC who have also agreed to investigate the cause of the disconnects and agreed to donate an uninterruptable power supply.

Through a 2014 questionnaire3, myself and a colleague identified a lack of skill by the second-year agrometeorology students in manipulating and analysing data and plotting graphs (Appendix 7 p34-35). This lack impeded teaching and mlearning in current and subsequent modules and other modules requiring analysis and graphical display of data.

3 UKZN Humanities and Social Sciences Research Ethics Committee protocol reference number HSS/0349/014

https://www.dropbox.com/sh/4iipodz3uhpys6v/AAAueojR0OvIw4uY3slSqkqAa?dl=0

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The technological age of today requires computer skills to handle large amounts of information that can be efficiently processed and stored using computers. Excel is an interface, between user and software, essential in communicating, analysing and synthesising data. It is regarded as one of the most powerful and most important software applications of all time and yet it receives scant attention at many institutions of higher learning.

Many students do not have the necessary skill in using Excel, widely regarded as an essential tool. Usually then, most staff decide not to involve Excel in their teaching. Perhaps modules could be taught quite differently, and learning could be very different, if the students had the necessary skill.

Based on experience, many students qualify for a degree that ill-equips them with tools to perform basic analyses of data and basic graph plotting. This needs to be rectified. Of greater concern: students are accepted into Honours or Masters programmes unable to analyse or graphically display data.

As a result of this initiative, the Supplementary Instruction section of our School have this year conducted an Excel course, specifically on handling data and producing graphs, for 100s of second year students (Westville campus). There are plans for a similar course for the Pietermaritzburg campus.

4 Methods of assessing students work and performance I have used various methods including tests, practicals and examination, using an external examiner, to assess student work. I provide detailed solutions and time for revision of tests. In addition, quizzes are used by the students to identify their knowledge gaps. There is also extensive revision of lecture material before each of the two tests and before the final examination. These revision sessions are usually outside the normal lecture periods. During revision sessions, knowledge gaps are identified by consensus with the class. Also, projects are an essential component of the overall assessment of student work. Even in first semester, second year, group research projects are used to introduce students to research and to working in teams. For each project, they elect a convener and they are assisted by a demonstrator and/or staff member. Groups are assisted at the weekly 3-h meetings with all members of the module or if necessary outside the normal timetabled periods. Almost all projects are based on aspects of the AIM system, and lecture content. Staff and demonstrators meet weekly to discuss project progress. In a second-semester second year module, students attempt a research project (50 % of overall mark). The project is externally examined and integral in assessing student work.

Student practical work also includes a scavenger hunt and extensive use of Excel. The hunt includes agro-environmental questions requiring interrogation of the AIM system screens. Proficiency in the use of Excel is assessed following six hours of instruction and several practicals that require data analysis and graph plotting. Practicals and projects form an important part of modules, are compulsory, and are marked and returned to students. Moodle is extensively used to provide students with soft copies of all lecture notes, lecture summaries, practical notes, quizzes, previous tests and previous examinations for use for improvement of their performance.

5 Evidence, impact and recognition of teaching and learning methods including AIM: Student and peer evaluation, publicity and community engagement

5.1 The result of the AIM system, including evaluation My published teaching and mlearning research describes the implementation, and assessment, of the AIM system that allows undergraduates (and postgraduates and academic staff) to view agrometeorological and other agro-environmental data, in table and graphical form, and extract data for downloading at any time and place.

Favourable comments and results of a 2013 questionnaires on system usage, friendliness and improvement are presented (Appendix 5 p30-32). Gratifying is that more than 80% of respondents indicated that they benefited from system use (Questions 13 to 16, Appendix 5, p31-32), that their appreciation of ranges of the various weather elements had improved, that system use had improved their ability to manipulate data in a spreadsheet and/or display data in graphic or table form, improved their appreciation/awareness of global climate change and/or global warming aspects and that system use had improved their appreciation/awareness of the graphical display, and trends, of agro-environmental and environmental data. What is also particularly gratifying, however, is the high percentage of 85% (93% for 2013, AMET210) of respondents indicating that use of the system had improved their appreciation of the ranges of various weather elements (Question 13, p31). It does mean

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that earlier exposure to AIM could assist further in the understanding of physical concepts of the agro-environment.

We are unaware of any similar system in Africa for the purposes described. The system developed at Utah State University (http://weather.usu.edu/htm/publicity), the first of its kind on a university campus and also launched in 2011, focuses on the reporting of agro-environmental measurements but does not allow data downloads by students. Besides feedback on the AIM system from students, and feedback through the publication and peer-review process, there has also been positive feedback through conference paper presentations.

5.2 Evidence: peer reports, student evaluations and awards

5.2.1 Videos and letters from past and current students Two videos are including as part of the evidence of good teaching and good postgraduate supervision (Appendix 8 p36 https://www.dropbox.com/sh/4iipodz3uhpys6v/ AAAueojR0OvIw4uY3slSqkqAa?dl=0: UKZN DTA.mp4). Letters from an undergraduate and a postgraduate student (both 2014) are self-explanatory and included (Appendix 9 p 37-38).

5.2.2 Peer evaluation of teaching Evaluation by colleague (Mr Clulow, Appendix 10 p 39-40) and nomination letter by the Head of School (Professor Modi, p41) are included. Both reports comment positively on my teaching abilities/strengths.

5.2.3 AIM system evaluation using UKZN-approved questionnaires Student feedback of AIM has always been very favourable (Appendix 5, p30-32). Most of the respondents of the first questionnaire were undergraduate students (73 %), for whom the system was designed, with 22 % being postgraduates and staff in equal proportion. The vast majority of users nearly 90 % found that the system was user-friendly with only 9.5 % needing to be shown how to use the system.

5.2.4 UKZN Quality Promotion and Assurance module evaluations using standard questionnaires Evaluations were done in all years but the AIM system was only in place in late 2011. Therefore, the first modules to be evaluated following implementation of AIM and the modified teaching methods for AMET210 (Agrometeorology and Environmental Biophysics) and AMET212 (Environmental Instrument) modules that I lectured was in 2013 (Appendix 11, p42-43). The average response for their core questions was 85.7 %. For questions directly on the lecturer (self), the average response was 89.6 %. For these questionnaires, the mean response across all of the 22 (core) questions was 4.0 (out of 5) (80 %) with a standard deviation of 0.36 (7.2 %) (AMET210 module) and 88.4 % with a standard deviation of 4.8 % (AMET212 module). More than 92 % (AMET210) and 81 % (AMET212) of the students rate the overall teaching effectiveness of the lecturer (self) as good and rate the overall quality of the modules as 89 % (AMET210) and 79 % (AMET212). For AMET210 (2013) there were 78 responses (88 % return), and for AMET212 there were 54 responses (87 %). For the ENVS318 (2014) Atmospheric Science module (Appendix 11 p44) there was an 88 % return with an average score of 85.5 % in spite of problems with this module beyond my control.

5.2.5 Excel instruction evaluation using a UKZN-approved questionnaire Following three practicals that included instruction on graph plotting and six hours of instruction, to four groups each of 30 second-year students, in the use of Excel for data analysis and graph plotting, all respondents (n = 93) indicated that the sessions were not a waste of time (Appendix 7 p34). The sessions were shared equally with a colleague. Student confidence in the use of Excel increased to 75.6 % and 90.8 % for Word. The standard of the lecturing for the sessions was judged high 90.6 %.

5.2.6 Awards for research on teaching and learning Two national awards based on the AIM system have been received: (a) A presentation by MJ Savage, based on the web-based AIM system, was judged by the Crop

Production Society of southern Africa the best presentation at the 2013 national Combined Congress of the Societies of Crop Science, Horticulture, Soil Science and Weed Science. The presentation was deemed the best out of 230 presentations: http://enewsletter.ukzn.ac.za/Story.aspx?id=121&storyid=1588 (ukznonline vol 7, issue 3, 2013).

http://weather.usu.edu/htm/publicityhttps://www.dropbox.com/sh/4iipodz3uhpys6v/%0bAAAueojR0OvIw4uY3slSqkqAa?dl=0https://www.dropbox.com/sh/4iipodz3uhpys6v/%0bAAAueojR0OvIw4uY3slSqkqAa?dl=0http://enewsletter.ukzn.ac.za/Story.aspx?id=121&storyid=1588

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(b) The paper by Savage (2012) on frost was judged the best published paper, making use of the AIM system, in the South African Journal of Plant and Soil. This national award was by the Board of the South African Society of Crop Production at the 2014 Combined Congress Soil Science, Crop Science, Horticultural Science and Weed Science Societies: http://ndabaonline.ukzn.ac.za/ UkzndabaStory/NdabaOnline-Vol2-Issue5/Agrometeorology%20Professor%20Wins%20Award %20for%20Best%20Paper%20Published%20in%202013/ (NdabaOnline vol 2, issue 5, 2014).

5.2.7 Descriptions of courses, modules or programmes developed I have developed all agrometeorology modules over several decades. While there have been major changes in the delivery of modules and the practicals and projects, over the last three and a half years, this has not resulted in significant changes to the syllabi of the agrometeorology modules.

5.3 Peer evaluation of teaching and learning through scholarship activities

5.3.1 Publication There has been peer review of and indirectly, there has been peer evaluation (and peer recognition) of my teaching (mlearning and research) activities through four published papers, one in-press paper and two peer-reviewed conference papers (Appendix 1 p20-22). Web-based teaching, learning and research using accessible real-time data obtained from field-based

agrometeorological measurement systems Michael J Savage, Michael G Abraha, Nicholas C Moyo,

Nile Babikir SAJ Plant and Soil 2014 31, 1323. DOI: 10.1080/02571862.2014.878757 http://www.tandfonline.com/eprint/zcrRzGscnEnDuuesbMrB/full

Nowcasting daily grass and air temperature minima MJ Savage Int J Biometeorology 2015 DOI

10.1007/s00484-015-1017-7

Estimation of frost occurrence and duration of frost for a short-grass surface MJ Savage SAJ Plant and Soil 2012a 29, 173181. DOI: 10.1080/02571862.2012.748938

http://www.tandfonline.com/eprint/WFSTDPxFAFv8AJFnWJyM/full

Estimation of leaf wetness duration for a short-grass surface MJ Savage SAJ Plant and Soil 2012b 29, 183189 DOI: 10.1080/02571862.2012.750017

http://www.tandfonline.com/eprint/TrYzCKyryCINrGAVy7kp/full

Microclimate conditions in ventilated wet-walled greenhouses in a sub-tropical climate: spatial variability MJ Savage SAJ Plant and Soil 2014a 3: 137143 DOI: 10.1080/02571862.2014.921942

Air temperature measurement errors MJ Savage (Peer-reviewed) Conference Proceedings of the South

African Society of Atmospheric Sciences 2013 1215. ISBN 978-0-620-56626-1.

A near real-time fire danger index measurement system S Strydom, MJ Savage 2013 Conference

Proceedings of the South African Society of Atmospheric Sciences 110113. ISBN 978-0-620-56626-1.

The paper by Savage et al. (2014) (Appendix 1 p20 bottom) contains a full description of the AIM system setup and description of use by students. It also touches on: data sharing, use of language, and potential for use of AIM in high/junior schools (Sections 3.3 and 3.4 p9). To some extent, the educational theory is included in this paper but was not fully developed. My masters dissertation goes into more detail. My teaching portfolio statement develops the philosophy and ideas even further and also proposes future research. One aspect, mentioned in the Teaching Portfolio Statement, which needs further investigation is the use of mlearning. To some extent, the AIM system is mlearning and probing personal use of AIM attempted to unpack that issue a high percentage of respondents indicated personal use of the system.

The paper on frost is based on the frost screen of AIM and was originally based on AMET210 and AMET212 projects (http://agromet.ukzn.ac.za:5355/?command=RTMC&screen=Frost). The material is used as part of the lecture content for AMET210.

The paper on leaf wetness was also originally based on an AMET212 project (http://agromet.ukzn.ac.za:5355/?command=RTMC&screen=Leaf%20wetness). The leaf wetness paper is part of AMET212.

A paper on greenhouse microclimate (Appendix 1 p 22 top), also based on AMET210 and AMET212 projects (Savage 2014), has as an objective the use of the AIM online data and information system. This aids research, illustrating measurement comparisons or measurement methods in near real-time, and also allows open data access to greenhouse users.

http://ndabaonline.ukzn.ac.za/%20UkzndabaStory/NdabaOnline-Vol2-Issue5/Agrometeorology%20Professor%20Wins%20Award%20%20for%20Best%20Paper%20Published%20in%202013/http://ndabaonline.ukzn.ac.za/%20UkzndabaStory/NdabaOnline-Vol2-Issue5/Agrometeorology%20Professor%20Wins%20Award%20%20for%20Best%20Paper%20Published%20in%202013/http://ndabaonline.ukzn.ac.za/%20UkzndabaStory/NdabaOnline-Vol2-Issue5/Agrometeorology%20Professor%20Wins%20Award%20%20for%20Best%20Paper%20Published%20in%202013/http://www.tandfonline.com/eprint/zcrRzGscnEnDuuesbMrB/fullhttp://www.tandfonline.com/eprint/WFSTDPxFAFv8AJFnWJyM/fullhttp://www.tandfonline.com/eprint/TrYzCKyryCINrGAVy7kp/fullhttp://agromet.ukzn.ac.za:5355/?command=RTMC&screen=Frosthttp://agromet.ukzn.ac.za:5355/?command=RTMC&screen=Leaf%20wetness

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5.3.2 Conference and workshop participation I was invited to participate in the UKZN UTLO workshop on: Innovative and Exemplary Research Teaching Practices in Undergraduate Curricula. The web-based AIM system was chosen as one of the innovative and exemplary practices that highlighted research teaching practices undertaken at UKZN.

I attended the Sixth Annual University Teaching & Learning Conference, UKZN, Durban, 25 to 27 September 2012. I also presented the paper: web-based teaching and learning early-warning system for real-time data and information for the agricultural, earth and environmental sciences.

Seven conference presentations highlight the use of mlearning in a tertiary environment but also the use of the AIM system for mlearning, teaching and research in a multilingual environment. Grant BR and MJ Savage. 2013. Estimation of sunshine duration from solar irradiance measurements

for implementation into a web-based environmental monitoring system. Paper, Combined Congress

2013, South African Society for Horticultural Sciences, Weed Science Society, Crop Production

Society and Soil Science Society of South Africa, 21 to 24 Jan, 2013, Durban. Paper, MJ Savage. Kaptein ND and MJ Savage. 2013. A web-based microclimatic measurement and evaporative cooling

control system in a forestry nursery. Paper, Combined Congress 2013, South African Society for

Horticultural Sciences, Weed Science Society, Crop Production Society and Soil Science Society of South Africa, 21 to 24 Jan, 2013, Durban. Paper, ND Kaptein.

Savage MJ. 2012. Web-based near real-time surface energy balance for short grass using surface

renewal, temperature variance and dissipation theory. Poster, ASA, CSSA and SSSA Annual Meetings (Cincinnati, Ohio, USA, 21 to 24 October, 2012). Presented by MJ Savage.

Savage MJ, Abraha MG, Moyo NC and Babikir ESN. 2012. Web-based teaching and learning early-

warning system for real-time data and information for the agricultural, earth and environmental

sciences. Sixth Annual University Teaching & Learning Conference, UKZN, Durban, 25 to 27 September 2012. Paper, MJ Savage.

Savage MJ. 2013. Air temperature measurement errors. Paper, South African Society of Atmospheric

Sciences, 26 to 27 Sept, 2013, Durban, South Africa. Paper, MJ Savage. Savage MJ. 2013. Web-based near real-time surface energy balance system above short grass. Poster

presentation to the Combined Congress 2013, South African Society for Horticultural Sciences,

Weed Science Society, Crop Production Society and Soil Science Society of South Africa, 21 to 24

Jan, 2013, Durban, South Africa. Paper, MJ Savage. Strydom S and Savage MJ. 2013. A near real-time fire danger index measurement system. Paper

presentation to the South African Society of Atmospheric Sciences, 26 to 27 Sept, 2013, Durban,

South Africa. Paper, S Strydom.

5.3.3 Unpublished materials

5.3.3.1 Dissertations based on the AIM system: completed and in progress/preparation

Web-based teaching, learning and research using real- time data from field-based agrometeorological

measurement systems MJ Savage MScAgric dissertation cum laude, University of KwaZulu-Natal.

Awarded April 2014 (relevant parts included in Appendices 1, 5 and 6).

Monitoring fire danger in near real-time using field-based agrometeorological measurement systems S Strydom MSc dissertation cum laude, University of KwaZulu-Natal. Awarded April 2015.

Human comfort: the natural environment and that of parked vehicles S Luthuli MSc dissertation in

preparation, University of KwaZulu-Natal. Planned submission December 2015. A web based soil water content measurement and control system for Eucalyptus dunnii seedlings in a

greenhouse ND Kaptein MSc dissertation in preparation, University of KwaZulu-Natal. Planned

submission May 2015. Radiation balance for open water L Myeni MSc dissertation in progress, University of KwaZulu-Natal.

Planned submission May 2016.

Fire meteorology S Strydom PhD in progress, University of KwaZulu-Natal. Planned submission

December 2016. Open water evaporation: a study at Midmar Dam JM Pasi PhD in progress, University of KwaZulu-

Natal. Planned submission December 2016.

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5.3.3.2 Thesis/dissertation template postgraduate supervision

The School Research Committee has accepted my paper: "A template style document for dissertations and theses" (School of Agricultural, Earth and Environmental Sciences). The purpose of the materials is to simplify and explain the process of writing a dissertation/thesis. The paper would assist postgraduates, supervisors, and even staff in the creation of long documents (Appendix 8 p36 and available as supplementary materials at https://www.dropbox.com/sh/04c7q76es5w7935/AAD64t7Kqf0tLFQn6zvpk0pIa?dl=0).

5.3.4 Videos, slides and other supplementary materials An animated Powerpoint slide show, videos, masters dissertation and PhD thesis templates, etc., listed in Appendix 8 (p36), are available as supplementary materials: slide shows: https://www.dropbox.com/sh/y8ic1swogdp655b/AABw-s33a3hoGiMUuLhUtHJpa?dl=0 videos: https://www.dropbox.com/sh/5oestvxmgw8xqjs/AADqXtLu6UsaZpt5LfNtp1Fna?dl=0

The AIM system (http://agromet.ukzn.ac.za:5355) is an innovative system that has specifically been developed for undergraduates for teaching and mlearning but also for the undergraduate project research. The system has also demonstrated potential for use by postgraduates. A complete set of slides, lecture notes, practical notes, tutorials for AMET210 and 212 are also made available to students using Moodle/Learn. These materials are contained in the supplementary materials see Appendix 8 (p36) for list.

5.3.5 Peer comment on contributions to curriculum development The masters dissertation on the AIM system that I submitted constituted peer comment of the curriculum

development of agrometeorology for the period 2011-2013. One of the examiners commented: "There

is no doubt that this is the most comprehensive, well-structured and well written dissertation that I have ever seen. The attention to detail is extraordinary, the publications emanating from the work are

impressive, and the contributions to teaching and community service are extremely laudable It is not

common to see new contributions made to science, as well as contributions to teaching, learning and

community service all in one dissertation. I award a summa cum laude Accept as is".

The second examiner commented: "This is an excellent MSc(Agric) thesis. The candidate (i) identified key challenges faced by university undergraduate/graduate students and (ii) developed a novel web based approach to teaching, learning and research to help teachers, students and researchers improve their particular skills and understanding of critical concepts in agrometeorology, the environmental and agriculture. A key component within this approach is a near real-time field-based agrometeorological measurement system developed by the candidate. He drew on his experience with this measurement system together with key literature, including papers he authored to produce this MSc thesis. Accept as is".

After graduation, the supervisor (Professor Colin S Everson) commented: "the masters thesis, which was accepted with no corrections, was of such a high quality that it far surpassed what one would expect from Masters-level research": http://ndabaonline.ukzn.ac.za/UkzndabaStory/Ndaba Online-Vol2-Issue24-College-of-CAES-PMB/Never%20too%20Old%20to%20Learn/

5.4 Recognition of excellence in teaching and learning

5.4.1 Recognition through invited seminars Unsolicited seminar invites have been received see Appendix 3 p26-7:

UKZN UTLO lecture, Pietermaritzburg April 2014;

Durban University of Technology lecture, Durban July 2014; Royal Society lecture, Pietermaritzburg September 2014;

Westfalia Technological Services, Tzaneen February 2015

Kranskop Farmers Association, Kranskop April 2015.

5.4.2 Peer recognition by UKZN: UTLO feature The UKZN Teaching and Learning Office (UTLO) decided in 2014 to web-highlight scholarship of teaching and learning and the AIM system was the first to be highlighted: http://utlo.ukzn.ac.za/SoTL/Prof_Michael_Savage.aspx (accessed 5 June 2014) (Appendix 12 p45-7).

https://www.dropbox.com/sh/04c7q76es5w7935/AAD64t7Kqf0tLFQn6zvpk0pIa?dl=0https://www.dropbox.com/sh/y8ic1swogdp655b/AABw-s33a3hoGiMUuLhUtHJpa?dl=0https://www.dropbox.com/sh/5oestvxmgw8xqjs/AADqXtLu6UsaZpt5LfNtp1Fna?dl=0http://agromet.ukzn.ac.za:5355/http://ndabaonline.ukzn.ac.za/UkzndabaStory/NdabaOnline-Vol2-Issue24-College-of-CAES-PMB/Never%20too%20Old%20to%20Learn/http://ndabaonline.ukzn.ac.za/UkzndabaStory/NdabaOnline-Vol2-Issue24-College-of-CAES-PMB/Never%20too%20Old%20to%20Learn/http://utlo.ukzn.ac.za/SoTL/Prof_Michael_Savage.aspx

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5.5 Student success data Histograms of module marks (AMET210, AMET212 and ENVS318) for period 2011-2014, but excluding 2012 when I was on sabbatical, are shown in Appendix 13 (p48). In spite of significantly increased student numbers and the significant increase in the BSocialScience students in 2013 and 2014, the pass rates in AMET210 and AMET212 have improved. For all years, the syllabi remained the same.

For AMET210, 34.7 % of the students obtained a mark of less than 50 % in 2010 (when AIM was not available) compared to an average of 28.0 % for the period 2011, 2013-4 when AIM was available.

For AMET212, 8.0 % of the students obtained a mark of less than 50 % in 2010 compared to an average of 4.8 % for the period 2011, 2013-4.

In both AMET210 and AMET212, there was a reduction in the number of students failing. In the case of AMET210, the use of the AIM system resulted in an increase from 12.2 % to 14.2 % of the students achieving a mark greater than 70 %.

Overall, for all modules, the failure rate was 21.4 % before introducing AIM and 16.7 % after AIM was introduced. This reduction could have been much more since there were many more BSocialSci students, in the more recent years compared to previously, many of whom lacked mathematics and the physical science skills and knowledge. The more conceptual modules (AMET210, ENVS318) were more difficult for students (average failure rate of 27.4 % and 18.6 % respectively) compared to the less conceptual and more practical module (AMET212) which has an average failure rate of 5.6 %.

5.6 Community engagement: educating the community in my field of expertise

5.6.1 Newspaper articles and other publicity Two letters to a