Journal
TEACHING IN HIGHER EDUCATION
Volume 25, Issue 4, Pages 527-540Publisher
ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
DOI: 10.1080/13562517.2019.1689388
Keywords
Datafication; learning analytics; data; platforms
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A common recommendation in critiques of datafication in education is for greater conversation between the two sides of the (critical) divide - what might be characterised as sceptical social scientists and (supposedly) more technically-minded and enthusiastic data scientists. This article takes the form of a dialogue between two academics representing these different perspectives - Dragan Gasevic (a data scientist who is one of the founders of the 'learning analytics' field) and Neil Selwyn (a social scientist and long-time critic of educational technology). Over the course of a six-month email exchange, we explore various arguments for and against the datafication of higher education. Thus, we are able to add a computational dimension to well-worn social criticisms of data representativeness, reductionism and injustice, as well as exploring social tensions inherent in technical claims to data-based precision, clarity and predictability. Crucially, these exchanges allow us to explore ways in which our two viewpoints converge, and therefore highlight opportunities for productive inter-disciplinary exchange and collaboration.
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