Enhancing Critical Thinking and Self‐Efficacy With <scp>GenAI</scp> : A Social Cognitive Perspective Using Structural Equation Modelling

Abstract

ABSTRACT Background The integration of Generative Artificial Intelligence (GenAI) into higher education is growing rapidly, yet its impact on learning processes remains underexplored. Existing research and theories, such as social cognitive theory (SCT), largely focus on human‐to‐human learning interactions, leaving a gap in understanding how cognitive and motivational mechanisms operate in human–AI contexts. Objectives This study investigates how GenAI features influence students' critical thinking and self‐efficacy, with a specific focus on the mediating role of cognitive engagement. Methods Drawing on SCT, we conceptualised GenAI features—playfulness, perceived learning value and output quality—as environmental stimuli influencing student outcomes via cognitive engagement. Survey data were collected from 223 undergraduate and postgraduate students. Structural equation modelling was used to test both direct effects and the mediating role of cognitive engagement. Results and Conclusions The results indicate that GenAI playfulness and perceived learning value significantly enhance students' cognitive engagement, which then positively affects their critical thinking and self‐efficacy. Cognitive engagement functioned as a key mediator in these relationships. However, output quality did not exhibit a significant effect, suggesting that engagement, rather than content quality alone, is crucial for fostering meaningful cognitive development. This study extends SCT by adapting it to human–AI learning contexts and provides actionable insights for designing GenAI tools that enhance learner engagement and development.

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