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Authentic Learning by Design: Meta-Requirements for AI Support for Students and Educators

Wolters, A.; Kipping, G.; Wass, S.; Gau, M.; Riehle, D. M.; Chandra Kruse, L.

Research article in edited proceedings (conference) | Peer reviewed

Abstract

Large language models (LLMs) have transformed learning and educational practices, yet concerns persist about whether authentic learning occurs when cognitive tasks are outsourced to artificial intelligence (AI) systems. We examined how AI systems can support educators in facilitating student’s authentic learning. This paper reports on the first two echelons of our echeloned design science research (eDSR). We evaluated 200 AI systems deployed across European educational institutions and interviewed 11 experienced educators in three countries. Based on the findings, we formulated and validated meta-requirements for AI systems that support authentic learning from the perspectives of students, educators, and educational institutions.

Details about the publication

Editors: vom Brocke J., Chandra Kruse L., Hevner A., Rosemann M., Chiarini Tremblay M. & Winter R.
Book title: Design for Better Futures: Beyond the Science of the Artificial. Completed Research
Page range: 227-245
Publisher: Springer International Publishing
Place of publication: Cham
Status: Published
Release year: 2026
Conference: 21st International Conference on Design Science Research in Information Systems and Technology, DESRIST 2026, Münster, Germany
Keywords: Authentic Learning; Design Science Research; Meta-Requirements; AI Learning Support; Pedagogical Design

Authors from the University of Münster

Kipping, Gregor
Chair of Information Systems and Business Process Management (Prof. vom Brocke) (BPM)