Fairness of Academic Performance Prediction for the Distribution of Support Measures for Students: Differences in Perceived Fairness of Distributive Justice Norms

Abstract

The availability of big data at universities enables the use of artificial intelligence (AI) systems in almost all areas of the higher education sector. This also applies to the prediction of academic performance of students: So-called Academic Performance Prediction (APP) uses machine learning methods to predict the academic performance of students from digital trace data available at universities. However, as the implementation of APP for the distribution of support measures for students is inevitably linked to considerations about distributive justice, we investigated in a large survey among German university students how the perceived fairness of APP differs depending on the distributive justice norm applied.

Marco Lünich

Social Scientist

My research interests include the public perception of Digital Media, Big Data, and Artificial Intelligence.