Abstract
The growing demand for business analytics (BA) graduates with strong data and problem-solving skills requires active learning for students. A typical, though infrequently used, element in university teaching is peer teaching by students. Since artificial intelligence (AI) is widely available and has a lower barrier to use than human feedback, the supportive use of AI could increase scalability, quality, and inclusivity. This teaching case, therefore, provides an overview of the state of research on the use of AI in IS teaching and illustrates the design principles of a university BA course for IS and accounting students with mixed AI student peer teaching. The course follows a prototype course with pure student peer review, based on case study work and a best-solution competition. The aim of this ongoing teaching project is to develop a replicable model for embedding AI into BA curricula.
Recommended Citation
Baumeister, Alexander; Walle, Gabriel; and Lorenz, Daniel, "AI as a Better Peer – The Use of Mixed AI-Student Peer Teaching in Learning Business Analytics" (2025). Proceedings of the 2025 Pre-ICIS SIGDSA Symposium. 70.
https://aisel.aisnet.org/sigdsa2025/70