Higher education institutions can use analytics to better predict which potential students are at greater risk of dropping out or failing, and impose some form of intervention. Institutions can employ analytics to categorise individual students using factors correlated with higher failure risk across a group, such as, for example, ethnicity, first-generation student and part-time student status. Institutions offering distance education have strong reasons to pursue risk analytics, with online learning providing increased access to data to facilitate analytics, and institutions desiring to improve retention for distance learners. Drawing on group-based risk analytics to propose or impose interventions for ‘risky’ students is an ethical concern if individual students are burdened solely due to group risk, without regard to them as individuals. Philosophers (Schauer, 2003; Lippert-Rasmussen, 2007, 2011, 2014) have argued there is little or no substantive difference between assessing individuals on group risk statistics and using more ‘individualised’ evidence.
This paper examines and rejects these arguments, identifying the (potential) compromising of individual agency and autonomy as distinctive ethical concerns with the use of group risk analytics. These concerns are discussed in the context of the emerging use of analytics to screen students in higher education. The paper proposes several measures that may mitigate the distinctive ethical concerns with analytics-based screening. These involve the transparency of the screening; the static or dynamic nature of the factors used in analytics; the use of statistics specific to individuals, and the distribution of responsibilities between the student and the institution.
Scholes, V. (2016). Analytics in higher education: The ethics of assessing individuals on group risk. In There and back: Charting flexible pathways in open, mobile and distance education. Conference proceedings (pp. 116–120). Hamilton, New Zealand: DEANZ. Retrieved from http://flanz.org.nz/flanzorg/wpcontent/uploads/2016/06/DEANZ16-Conferenceproceedings11-April.pdf