Hybrid Intelligence in Higher Education: Exploring Disciplinary and Experiential Determinants of Students’ AI Acceptance

The integration of artificial intelligence (AI) in higher education is no longer a question of 'if', but of 'how'. Specifically, which roles humans and technology can and should play. Based on a survey of 731 students across diverse disciplines, this study explores how prior AI experience and field of study influence students’ acceptance of hybrid teaching models. While 84% reject AI-only instruction, 62% support a collaborative model combining human and machine intelligence. Drawing on Task-Technology Fit (TTF) and Hybrid Intelligence theory, we demonstrate that acceptance is driven less by novelty and more by perceived educational value. Students with prior AI exposure report significantly higher acceptance of hybrid instructional formats, especially in management-oriented disciplines. Our findings offer empirically grounded guidance for developing ethically grounded, effective AI-assisted learning environments that complement rather than replace human instruction.