Educational Technology Research and Development

, Volume 64, Issue 6, pp 1083–1106 | Cite as

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

  • Negin MirriahiEmail author
  • Daniyal Liaqat
  • Shane Dawson
  • Dragan Gašević
Research Article


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.


Instructional norms Learning technology Video annotation Learning analytics Higher education 



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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Copyright information

© Association for Educational Communications and Technology 2016

Authors and Affiliations

  • Negin Mirriahi
    • 1
    Email author
  • Daniyal Liaqat
    • 2
  • Shane Dawson
    • 3
  • Dragan Gašević
    • 4
    • 5
  1. 1.School of Education & Learning and Teaching UnitUNSWSydneyAustralia
  2. 2.Department of Computer ScienceUniversity of TorontoTorontoCanada
  3. 3.Teaching Innovation UnitUniversity of South AustraliaAdelaideAustralia
  4. 4.Moray House School of EducationUniversity of EdinburghEdinburghUK
  5. 5.School of InformaticsUniversity of EdinburghEdinburgh, MidlothianUK

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