From threat to tool: AI self-efficacy and user profiles in higher education
Generative artificial intelligence (GenAI) has brought both challenges and opportunities for teachers in higher education. This study does not focus on restrictive methods; instead, it explores how educators can actively promote academic integrity. We contend that AI self-efficacy, characterized as a student’s confidence in their capacity to employ AI ethically and efficiently, constitutes a substantial determinant. This paper delineates significant findings derived from a survey administered by 177 university students. A moderation analysis indicates that the adverse correlation between AI usage frequency and academic integrity is markedly diminished among students exhibiting high AI self-efficacy. Moreover, a cluster analysis clearly delineates three distinct AI user profiles: Confident and Cautious Users, Pragmatic High Users, and Dependent Users. Demographic studies reveal a significant correlation between these profiles and the students’ academic disciplines. The results suggest that the focus of instruction should transition from a “one-size-fits-all” approach to tailored interventions designed to enhance student empowerment. This article outlines practical implications and customized strategies for each student profile.