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Uncovering student learning profiles with a video annotation tool: reflective learning with and without instructional norms

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Abstract

This study explores the types of learning profiles that evolve from student use of video annotation software for reflective learning. The data traces from student use of the software were analysed across four undergraduate courses with differing instructional conditions. That is, the use of graded or non-graded self-reflective annotations. Using hierarchical cluster analysis, four profiles of students emerged: minimalists, task-oriented, disenchanted, and intensive users. Students enrolled in one of the courses where grading of the video annotation software was present, were exposed to either another graded course (annotations graded) or non-graded course (annotations not graded) in their following semester of study. Further analysis revealed that in the presence of external factors (i.e., grading), more students fell within the task-oriented and intensive clusters. However, when the external factor is removed, most students exhibited the disenchanted and minimalist learning behaviors. The findings provide insight into how students engage with the different features of a video annotation tool when there are graded or non-graded annotations and, most importantly, that having experience with one course where there are external factors influencing students’ use of the tool is not sufficient to sustain their learning behaviour in subsequent courses where the external factor is removed.

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Notes

  1. For the purpose of the study presented in this paper, we have adopted Garrison and Vaughan's (2008) definition of blended learning as the “integration of thoughtfully selected and complementary face-to-face and online approaches and technologies” (p. 148).

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Acknowledgments

This research is in part supported by Australian Office of Learning and Teaching (Innovation and Development Grant), Canada Research Chair Program of the Government of Canada, Social Sciences and Humanities Research Council of Canada (Insight Grant), and Natural Sciences and Engineering Research Council of Canada (Discovery Grant). We also thank Thomas Dang for data extraction.

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Authors and Affiliations

  1. School of Education & Learning and Teaching Unit, UNSW, Sydney, NSW, 2052, Australia

    Negin Mirriahi

  2. Department of Computer Science, University of Toronto, 10 King’s College Road, Rm 3302, Toronto, ON, M5S 3G4, Canada

    Daniyal Liaqat

  3. Teaching Innovation Unit, University of South Australia, 160 Currie Street, Adelaide, SA, 5000, Australia

    Shane Dawson

  4. Moray House School of Education, University of Edinburgh, Holyrood Rd, Edinburgh, EH8 8AQ, UK

    Dragan Gašević

  5. School of Informatics, University of Edinburgh, 10 Crichton St, Edinburgh, Midlothian, EH8 9AB, UK

    Dragan Gašević

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  1. Negin Mirriahi
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Correspondence to Negin Mirriahi.

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Mirriahi, N., Liaqat, D., Dawson, S. et al. Uncovering student learning profiles with a video annotation tool: reflective learning with and without instructional norms. Education Tech Research Dev 64, 1083–1106 (2016). https://doi.org/10.1007/s11423-016-9449-2

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