Artificial Intelligence Over-Reliance Mediates Performance Expectancy, Social Influence, and Inert Thinking in University Students - Novianti, Andi Fitri; Mappeasse, Muhammad Yusuf; Fakhri, M. Miftach; Jannah, Devi Miftahul (Universitas Islam Negeri Raden Intan Lampung, 2026)
The rapid integration of artificial intelligence (AI) in higher education is reshaping students’ learning behaviors and cognitive engagement. Although AI tools enhance academic efficiency, excessive reliance on these technologies may unintentionally foster inert thinking by reducing independent cognitive processing. This study investigates the mediating role of over-reliance on artificial intelligence in the relationship between performance expectancy, social influence, and inert thinking among university students. A quantitative cross-sectional survey was conducted with 342 undergraduate students from multiple universities. Data were collected using a structured questionnaire grounded in technology acceptance theory and cognitive learning perspectives and analyzed through Partial Least Squares Structural Equation Modeling (PLS-SEM). The results indicate that performance expectancy and social influence significantly predict students’ over-reliance on AI, which in turn significantly mediates their relationship with inert thinking tendencies. These findings suggest that while AI-supported learning environments improve task performance, excessive dependence on AI may weaken students’ independent cognitive engagement. This study contributes empirical evidence to the emerging literature on AI-mediated learning by clarifying the cognitive risks associated with AI dependency and highlighting the importance of designing balanced AI-integrated instructional environments that promote responsible use while sustaining critical thinking development.