Individually recommended? – How AI-based Advisory Systems affect Student Diversity – ADVICE
In various areas, AI-based advisory systems can help to scour big amounts of data, to match these with individual peculiarities and to provide individualized recommendations based on this. At the same
time, due to a shortened or distorted data basis or due to insufficient implementation, they carry the risk to only suggest standard pathways and thus to insufficiently map diversity in society. The present research project aims to find out how to implement and design AI-based advisory systems at universities in order to give students valuable suggestions for their further study path while supporting the diversity of the student population. For this purpose, a subproject on each data quality, the acceptance of AI-based systems and the investigation of study course analyzes will be conducted in the phase of the Planning Grant. In addition, the Planning Grant will help to specify the research questions, the related research methods and the research group for the Full Grant and to establish a common language among the partners.
Project team: Sven Laumer, Karl Wilbers, Tobias Wolbring