Individually recommended? - How AI-based advisory systems affect student diversity (ADVICE)
Third Party Funds Group - Overall project
Acronym: ADVICE
Start date : 01.03.2020
End date : 28.02.2021
Project details
Scientific Abstract
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.
Involved:
Sven Laumer
Project Leader
Karl Wilbers
Project Leader
Tobias Wolbring
Project Leader
Daniel Schömer
Project Member
Edgar Treischl
Project Member
Jonas Weigert
Project Member
Contributing FAU Organisations:
Lehrstuhl für Empirische Wirtschaftssoziologie
Schöller Endowed Chair for Information Systems (Digitalization in Business and Society)
Lehrstuhl für Wirtschaftspädagogik und Personalentwicklung
