Ethics in Predictive Learning Analytics

Abstract

Most universities collect large amounts of students' data to enhance teaching, understand student behaviour, and predict their success. However, such practices raise privacy and ethical issues due to sensitive data harvesting practices. Despite the recognised importance of this topic, few empirical studies address how students perceive the ethical issues related to predictive learning analytics (PLA). To redress this, interview data collected from 42 undergraduate and postgraduate students in a Northern Irish university were thematically analysed. Findings suggest that there are at least three distinct groups of students having varying assumptions about ethics in PLA. They are (1) naïve and trusting, (2) cautious and compromising, and (3) enlightened and demanding, and all of them tend to narrowly focus only on the issue of informed consent. An empirically supported argument for the need for PLA researchers to recognise the within-group variations in student populations and to educate all types of students in issues related to ethics is presented.