Which datasets are preferred by university students in Learning Analytics Dashboards? A Situated Learning Theory Perspective

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Abstract

Scholarly interests in developing personalised learning analytics dashboards (LADs) in universities have been increasing. LADs are data visualisation tools for both teachers and learners that allow them to support student success and improve teaching and learning. In most LADs, however, a teacher-centric, institutional view drives their designs, while treating students only as passive end-users, which results in LADs being less useful to students. To address this limitation, we used a card sorting technique and asked 42 students at a university in Northern Ireland to construct dashboards that reflect their priorities. Using a situated theory of learning as a lens, and with the help of multiple qualitative methods, we collected data on what constitutes useful dashboards. Findings suggest that situated learning datasets, such as information on how students learn by talking and listening to others in their communities, need to be integrated into LADs. Students preferred to see the inclusion of qualitative narratives, self-directed learning data and financial information (money spent vs resources utilised) in LADs. As well as raising new questions on how such LADs could be designed, this study challenges institutional overreliance on measurable digital footprints as proxies for academic success. We call for recognising the wider social learning that happens in landscapes of practice so that LADs become more useful to students.
Original languageEnglish
Pages (from-to)1-26
Number of pages30
JournalINFORMS Transactions on Education
Early online date11 May 2023
DOIs
Publication statusPublished online - 11 May 2023

Keywords

  • personalisation
  • student-led design
  • student engagement
  • customised design
  • learning analytics dashboards
  • situated theory of learning

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