<![CDATA[This study addresses the growing reliance on artificial intelligence (AI) in education by re-examining the behavioral mechanisms that drive its actual use. While perceived behavioral control has long been treated as a primary determinant of technology adoption, its explanatory power in complex and less transparent systems such as AI remains limited. This study advances the argument that behavioral capability alone is insufficient and must be understood in conjunction with trust-based evaluations. Accordingly, it investigates how perceived behavioral control influences AI usage both directly and indirectly through brand trust. Data were collected from 317 university students in mathematics-related programs and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results reveal that although perceived behavioral control significantly affects both trust and usage, brand trust exerts a stronger and more decisive influence on actual behavior. The mediation analysis further shows that trust functions as a critical transmission mechanism, partially mediating the relationship between perceived behavioral control and AI usage. These findings challenge the conventional assumption that capability is the dominant driver of behavior and instead highlight the central role of trust in shaping engagement with AI. By demonstrating a dual-pathway mechanism, this study extends behavioral theory in the context of intelligent systems. The results underscore that successful AI adoption depends not only on users’ ability to operate the technology but also on their confidence in its reliability and credibility. ]]>
