Beyond Barriers: How Risk Perceptions Moderate Students’ Generative AI Adoption in Higher Education

• In Event: Technology and Student Learning

Abstract

The rise of generative AI (GenAI) in higher education presents both challenges and opportunities, yet a gap remains between policy responses and students’ real perceptions. This study explores how perceived usefulness, multidimensional risk perceptions, and behavioral intention interact in GenAI adoption among university students. We validated a four-factor risk model: academic integrity, information quality, cognitive development, and technical security. Results show that (1) perceived usefulness strongly predicts adoption intention; (2) perceived risks exert a modest negative effect; and (3) risk dimensions significantly moderate the usefulness–intention link. Rather than deterring use, risk awareness fosters more thoughtful engagement with GenAI, highlighting the importance of student-centered, evidence-based policy design.

Author

• Jie Lin, Shanghai Jiao Tong University