Learning analytics: challenges and limitations

Wilson, Anna; Watson, Cate; Thompson, Terrie Lynn; Drew, Valerie; Doyle, Sarah

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.

Citation

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

• Journal Article Type: Article
• Acceptance Date: May 10, 2017
• Online Publication Date: May 24, 2017
• Publication Date: Nov 17, 2017
• Deposit Date: Mar 7, 2019
• Publicly Available Date: Mar 7, 2019
• Journal: Teaching in Higher Education
• Print ISSN: 1356-2517
• Electronic ISSN: 1470-1294
• Publisher: Routledge
• Peer Reviewed: Peer Reviewed
• Volume: 22
• Issue: 8
• Pages: 991-1007
• DOI: https://doi.org/10.1080/13562517.2017.1332026
• Keywords: learning analytics; big data; sociomaterial; professional learning
• Public URL: http://researchrepository.napier.ac.uk/Output/1401336