<![CDATA[The pervasive integration of Generative Artificial Intelligence (GenAI) across higher education institutions has fundamentally transformed student knowledge acquisition, cognitive processing, and academic engagement. While conversational AI systems offer dynamic cognitive scaffolding and personalized feedback, uncalibrated reliance threatens to foster cognitive offloading and diminish independent critical inquiry. Grounded in Social Cognitive Theory, the Community of Inquiry (Practical Inquiry Cognitive Presence) framework, and Self-Regulated Learning Theory, this study empirically investigates the structural dynamics connecting Generative AI Literacy to Students’ Critical Thinking, explicitly evaluating the explanatory mediating mechanism of AI-Supported Learning Engagement. Employing an explanatory sequential mixed-methods design, quantitative data were gathered from undergraduate students (N = 115 survey cohort; benchmarked against multi-institutional structural parameters, N = 623) and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM), followed by qualitative thematic analysis of student interaction scripts and semi-structured interviews (N = 10). The empirical results demonstrate that Generative AI Literacy significantly and positively predicts both AI-supported learning engagement (β = 0.668, p < 0.001) and critical thinking (β = 0.479, p < 0.001). Furthermore, AI-supported learning engagement exerts a strong direct effect on critical thinking (β = 0.353, p < 0.001) and functions as a statistically significant partial mediator (β = 0.240, p < 0.001). Crucially, qualitative findings illuminate that engagement quality specifically the distinction between mindful engagement (evaluative auditing, prompt refinement, and hypothesis testing) and unreflective engagement (automated output submission) determines whether GenAI acts as a dialectical partner or a cognitive substitute. Mindful engagement enables students to bridge the critical 'Resolution Gap' across inquiry phases. This research establishes that AI literacy serves as an essential epistemic regulator, providing higher education institutions with actionable frameworks for process-oriented assessment, ethical AI integration, and pedagogical design. ]]>
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