Xi Chen, Mingyue Cui, Pu Sun, Xiaohong Xu, Ke Ma, Yan Li
BACKGROUND: With the rapid integration of generative artificial intelligence (GenAI) into higher education, understanding how technology shapes students’ psychological motivation has become increasingly critical. Self-control is widely recognized as a core internal resource that sustains academic engagement, yet little is known about how this self-regulatory capacity operates when external technological reliance intervenes in learning. Addressing this gap, the present study introduces an innovative framework that integrates Self-Determination Theory (SDT) and Path Dependence Theory (PDT) to examine how meaning in life—defined as individuals’ perceived sense of purpose, coherence, and value in life—mediates the relationship between self-control and academic engagement, and how GenAI dependence moderates this pathway. This approach provides a novel perspective on the interaction between inner volitional strength and external technological dependence in shaping academic motivation. METHOD: A cross-sectional survey was conducted among 1,139 university students in China. Validated self-report questionnaires were used to assess self-control, meaning in life, GenAI dependence, and academic engagement. Structural equation modeling (SEM) was performed using Mplus 8.3 to construct latent variables and test the hypothesized moderated mediation model. RESULTS: The findings indicated that self-control significantly predicted academic engagement. Meaning in life partially mediated this relationship. Furthermore, GenAI dependence negatively moderated the pathway from self-control to meaning in life—specifically, the positive effect of self-control on meaning in life was weaker among students with higher GenAI dependence. These results reveal a dynamic interaction between internal psychological strengths and external technological reliance in shaping academic engagement. CONCLUSION: This study proposes and validates a novel moderated mediation mechanism linking self-control, meaning in life, and academic engagement within the emerging context of AI-augmented learning. By integrating motivational and technological perspectives, it contributes a new theoretical model of “motivational regulation under technological mediation.” Practically, the findings underscore the dual importance of cultivating students’ self-regulation and existential meaning-making capacity while promoting reflective and autonomous GenAI use. These insights offer evidence-based guidance for fostering sustainable academic motivation and psychological well-being in digitalized higher education environments.