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.
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.
Keywords
Authentic Learning; Design Science Research; Meta-Requirements; AI Learning Support; Pedagogical Design
Cite as
Wolters, A., Kipping, G., Wass, S., Gau, M., Riehle, D. M., & Chandra, K. L. (2026). Authentic Learning by Design: Meta-Requirements for AI Support for Students and Educators. In vom Brocke, J., Chandra, K. L., Hevner, A., Rosemann, M., Chiarini, T. M., & Winter, R. (Eds.),
Design for Better Futures: Beyond the Science of the Artificial. Completed Research (pp. 227–245). Cham: Springer International Publishing.
Details
Publication type
Research article in proceedings (conference)
Peer reviewed
Yes
Publication status
Published
Year
2026
Conference
21st International Conference on Design Science Research in Information Systems and Technology, DESRIST 2026
Venue
Münster
Book title
Design for Better Futures: Beyond the Science of the Artificial. Completed Research
Editor
vom Brocke J., Chandra Kruse L., Hevner A., Rosemann M., Chiarini Tremblay M. & Winter R.
Start page
227
End page
245
Publisher
Springer International Publishing
Place
Cham
DOI
