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Learning Analytics within Higher Education: Autonomy, Beneficence and Non-maleficence

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Abstract

Higher education institutions are increasingly relying on learning analytics to collect voluminous amounts of data ostensibly to inform student learning interventions. The use of learning analytics, however, can result in a tension between the Council for the Advancement of Standards in Higher Education (CAS) principles of autonomy and non-malfeasance on the one hand, and the principle of beneficence on the other. Given the complications around student privacy, informed consent, and data justice in addition to the potential to do harm, many current practices around learning analytics within higher education can be considered to be in violation of CAS standards. This paper aims to explore this tension in greater detail and argues that the student voice offers a promising way to ensure that students’ autonomy is respected, harm is reduced, and that higher education institutions can still fulfil the principle of beneficence.

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  1. Baylor University, Waco, Texas, USA

    Kevin O’Donoghue

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Correspondence to Kevin O’Donoghue.

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O’Donoghue, K. Learning Analytics within Higher Education: Autonomy, Beneficence and Non-maleficence. J Acad Ethics 21, 125–137 (2023). https://doi.org/10.1007/s10805-021-09444-y

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