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GenAI in Higher Education: A Review of Student Adoption and A Future Research Agenda
0
Zitationen
7
Autoren
2025
Jahr
Abstract
The rapid proliferation of Generative Artificial Intelligence (GenAI) has created a fragmented and quickly evolving research landscape in higher education, where foundational models like TAM and UTAUT show significant gaps. To address this, we conducted a Systematic Literature Review (SLR) following PRISMA principles, synthesizing 87 empirical studies on student adoption from November 2022 to May 2024. Our analysis reveals five core themes: foundational acceptance, psychological factors, ethical risks, pedagogical opportunities, and contextual influences. We confirm that while Performance and Effort Expectancy are primary drivers, their impact is critically mediated by psychological states such as Trust and AI Anxiety. Furthermore, we identify a significant “disciplinary divide” in usage patterns between STEM and Non-STEM students. This review provides a comprehensive map of the field, deconstructs key adoption pathways, and concludes with a structured research agenda.
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