Responsible Academic Performance Predicton (RAPP) - A Socially Responsible Approach to the Introduction of Student Performance Predicton at a German Higher Education Institution
Academic Performance Prediction (APP) systems as supporting AI systems in higher education promise the early detection of potential failures and thus enable a targeted use of resources by the university to prevent them through individual support measures. However, according to a study conducted at Heinrich Heine University, the use of AI-based systems is considered problematic by students as far as their own data and planning are concerned. This represents a serious obstacle to the use and success of such systems. The aim of this project is therefore a socially acceptable use of AI systems, for which ethical aspects and their perception by those affected are to be researched. For this purpose, on the one hand, an AI system for academic performance prediction will be developed based on corresponding preliminary work, in which a rule-based explanation component will create extensive transparency for those affected. On the other hand, the use of this system, the necessary data for prediction according to technical and ethical aspects, and the perception by the students will be investigated through laboratory and field experiments. From this, recommendations for action will ultimately be derived in collaboration with the responsible bodies in the university for the use of such systems.