This study is an investigation of the influencing factors of AI tools adoption among university students, particularly in their learning, and it investigates the adoption's relationship to their critical thinking and engagement in learning. The study is underpinned by the Theory of Planned Behavior (TPB) with additional integration of contextual antecedents, namely, accessibility, education and training, ethical awareness, cognitive development, and cultural perspectives, in a framework that explains behavior and cognition. It is an exploratory sequential mixed-method study that combines qualitative interviews involving 30 Saudi university students and a quantitative survey of 728 students. The data obtained was tested using Structural Equation Modeling (Smart PLS 4.0) to validate the proposed study model. Based on the findings of the analysis, the top predictors of students' intention to use AI tools are attitude, subjective norms, and perceived behavioral control, whereas critical-thinking engagement is predicted by the positive effect of intention. The major contextual factors in forming TPB constructs are accessibility, training, and ethical awareness, with cultural perspectives supporting the normative influence of both peers and instructors. The moderation analysis indicates that age does not significantly condition the relationships in the model, while gender shows a limited moderating effect only on the relationship between subjective norms and behavioral intention. Overall, these findings suggest that demographic moderators play a minimal role in shaping AI adoption intentions in this context. Through the findings, TPB was extended through the confirmed relationships between behavioral intention and cognitive outcomes, and the revelation that responsible and reflective AI can improve the critical engagement of students. Furthermore, the study findings also extend theory through the contextualization of TPB with an educational setting that is different from a Western one. The study also contributes to practice by emphasizing the requirement for AI integration initiatives and strategies that are ethical, inclusive, and pedagogical.
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