Privacy and Analytics – it’s a DELICATE issue. A Checklist to establish trusted Learning Analytics
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TL;DR
The efforts of Hendrik Drachsler have been partly funded by the EU FP7 LACE-project and by the EP4LA workshop series.
Abstract
The widespread adoption of Learning Analytics (LA) and Educational Data Mining (EDM) has somewhat stagnated recently, and in some prominent cases even been reversed following concerns by governments, stakeholders and civil rights groups. In this ongoing discussion, fears and realities are often indistinguishably mixed up, leading to an atmosphere of uncertainty among potential beneficiaries of Learning Analytics, as well as hesitations among institutional managers who aim to innovate their institution’s learning support by implementing data and analytics with a view on improving student success. In this paper, we try to get to the heart of the matter, by analysing the most common views and the propositions made by the LA community to solve them. We conclude the paper with an eight-point checklist named DELICATE that can be applied by teachers, researchers, policy makers and institutional managers to facilitate a trusted implementation of Learning Analytics.
