Corresponding Manager: Mareike Mueller (m.mueller@macromedia.de)
Track Manager(s): Mareike Mueller, Astrid Friese, Anna-Luisa Stoeber
Description
Digital transformation in educational settings is accelerating through generative AI and learning analytics. Institutions face a dual challenge: fostering human–AI collaboration that enhances teaching and learning while safeguarding academic integrity, ethics, and human agency. This track invites empirical and conceptual contributions examining the synergy between human and artificial intelligence in higher education; what we call Hybrid Intelligence. We welcome studies exploring how disciplinary context, experience, or institutional culture shape the acceptance, trust, and effectiveness of AI in teaching and assessment. The track builds on evidence that students and educators increasingly favor hybrid, human-in-the-loop models over AI-only instruction. Integrating frameworks such as Task–Technology Fit (TTF), Hybrid Intelligence, and Technology Acceptance Models (UTAUT, TAM), the track bridges technical, pedagogical, and ethical perspectives. Key topics include human–AI collaboration in education, AI literacy, governance and transparency, trust and fairness, cross-cultural adoption studies, and the “dark side” of AI; academic integrity, cognitive offloading, and data ethics.
Keywords
AI in Educational Institutions; Hybrid Intelligence; Task-Technology Fit; Digital Pedagogy; Ethical AI
Key References
Müller, M., & Mütterlein, J. (2025). Enhancing higher education through AI: A longitudinal study on student performance and acceptance [Conference presentation]. DTS Conference 2025, Paris School of Business & DISAQ – University Parthenope, Paris, France.
Stöber, A. & Friese, A. (2025). Impact of Artificial Intelligence on Management Education and the role of educators [Conference presentation]. DTS Conference 2025, Paris School of Business & DISAQ – University Parthenope, Paris, France.
Müller, M., & Mütterlein, J. (2026). Hybrid Intelligence in Higher Education: Exploring Disciplinary and Experiential Determinants of Students’ AI Acceptance. In Proceedings of the 59th Hawaii International Conference on System Sciences (HICSS-59). Accepted paper. University of Hawaiʻi at Mānoa.
Stöber, A. & Friese, A. (2026). From Lecturers to Learning Architects: Rethinking Educator Roles in the Age of AI. In Proceedings of the 59th Hawaii International Conference on System Sciences (HICSS-59). Accepted paper. University of Hawaiʻi at Mānoa.