AIStudyBuddyCopyright: © LuFgi9
The AIStudyBuddy project uses modern AI technologies to support the individual planning and reflection of study paths. The project is a joint project of RWTH Aachen University, Bergische Universität Wuppertal (BUW) and Ruhr-Universität Bochum (RUB) and is part of the federation and state initiative for the promotion of artificial intelligence in higher education. Funding of approximately 3.9 million euros is provided by the German Federal Ministry of Education and Research and the project sponsor VDI/VDE-IT.
The project focuses on two target groups:
- Students are provided with StudyBuddy, a tool for informed, evidence-based planning of their own studies. It offers graphical representations of study progress and provides actionable feedback. This is based on rule-based study progress plans as well as progress profiles determined by AI technology, which lead to successful study completions. Generic study plans are thus supplemented by a tool for individual study planning that is continuously adapted, justified and reflected upon.
- With BuddyAnalytics, study program designers receive an interactive tool that supports planning decisions such as competency-based curriculum development and academic advisory services. By analyzing and visualizing study program data from different higher education systems, adjustments and improvements to study programs can be developed in an evidence-based manner.
For this purpose, the project combines AI paradigms of data-driven (process mining) and rule-based AI (answer set programming, ASP). Process mining analyzes study behavior using data from campus management systems, learning management systems, and examination systems. It contrasts real study paths with intended ones. Answer Set Programming is used to generate transparent rationales for feedback that can be understood by non-domain experts. All components are part of a reference architecture that follows principles such as ethics-by-design and privacy-preservation.
The project is developed and researched in interdisciplinary collaboration of computer science, (higher education) didactics, ethics and educational economics. The project team members of our research group are responsible for the user-centered design and development of StudyBuddy and BuddyAnalytics as well as for the conceptual design and implementation of the reference architecture. Special attention is given to the interfaces to the AI technologies to be used as well as to the iterative development and research according to design-based research.
Our project team
Prof. Dr.-Ing. Ulrik Schroeder (Scientific Project lead)
René Röpke (Project lead i9)
Prof. Dr. Wil van der Aalst, Chair for Process and Data Science (PADS), RWTH Aachen
Prof. Gerhard Lakemeyer, Ph.D., Knowledge Based Systems Group (KBSG), RWTH Aachen
PD Dr. Malte Persike (Overall project management), Center für Lehr-Lern-Services (CLS), RWTH Aachen
Prof. Dr. Kerstin Schneider, Wuppertal Research Institute for the Economics of Education (WIB), BUW
Dr. Simon Görtz, Dez. 6 - Studium, Lehre und Qualitätsmanagement, BUW
Prof. Dr. Maren Scheffel, Educational Data Science (EDS), RUB
Prof. Dr. Sebastian Weydner-Volkmann, Ethics of Digital Methods and Technologies (EDMT), RUB
Dr. Peter Salden, Centre for Teaching and Learning (ZfW), RUB