Learning analytics: ethical issues and dilemmas

Slade, Sharon and Prinsloo, Paul (2013). Learning analytics: ethical issues and dilemmas. American Behavioral Scientist, 57(10) pp. 1509–1528.

DOI: https://doi.org/10.1177/0002764213479366


The field of learning analytics has the potential to enable higher education institutions to increase their understanding of their students’ learning needs and to use that understanding to positively influence student learning and progression. Analysis of data relating to students and their engagement with their learning is the foundation of this process. There is an inherent assumption linked to learning analytics that knowledge of a learner’s behavior is advantageous for the individual, instructor and educational provider. It seems intuitively obvious that a greater understanding of a student cohort and of the learning designs and interventions to which they best respond would be of benefit to students and, in turn, for the retention and success rate of the institution. Yet, such collection of data and its use faces a number of ethical challenges, including issues of the location and interpretation of data; informed consent, privacy and the de-identification of data; and the classification and management of data.

Approaches taken to understand the opportunities and ethical challenges of learning analytics necessarily depend on a range of ideological assumptions and epistemologies. This paper proposes a socio-critical perspective on the use of learning analytics. Such an approach highlights the role of power, the impact of surveillance, the need for transparency and an acknowledgment that student identity is a transient, temporal and context-bound construct. Each of these affects the scope and definition of the ethical use of learning analytics. We propose six principles as a framework for a number of considerations to guide higher education institutions to address ethical issues in learning analytics and challenges in context-dependent and appropriate ways.

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