Learning analytics: challenges and limitations

Anna Wilson, Cate Watson, Terrie L. Thompson, Valerie Drew, Sarah Doyle

Research output: Contribution to journalArticle

21 Citations (Scopus)
20 Downloads (Pure)

Abstract

Learning analytic implementations are increasingly being included in learning management systems in higher education. We lay out some concerns with the way learning analytics – both data and algorithms – are often presented within an unproblematized Big Data discourse. We describe some potential problems with the often implicit assumptions about learning and learners – and indeed the tendency not to theorize learning explicitly – that underpin such implementations. Finally, we describe an attempt to devise our own analytics, grounded in a sociomaterial conception of learning. We use the data obtained to suggest that the relationships between learning and the digital traces left by participants in online learning are far from trivial, and that any analytics that relies on these as proxies for learning tends towards a behaviourist evaluation of learning processes.
Original languageEnglish
Pages (from-to)991-1007
Number of pages17
JournalTeaching in Higher Education
Volume22
Issue number8
Early online date24 May 2017
DOIs
Publication statusPublished - 17 Nov 2017
Externally publishedYes

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Wilson, A., Watson, C., Thompson, T. L., Drew, V., & Doyle, S. (2017). Learning analytics: challenges and limitations. Teaching in Higher Education, 22(8), 991-1007. https://doi.org/10.1080/13562517.2017.1332026