Ning Wang
AIL was positively associated with college students' AIA, and this association was partially accounted for by independent and sequential indirect paths through PA and GM. Moreover, AIL demonstrates a marked heterogeneous structure, with distinct latent classes exhibiting divergent patterns in path analysis. These findings provide empirical evidence for applying affordance theory and implicit theories of intelligence to the context of human AI collaboration, and suggest potential implications for differentiated AI education and mindset interventions in higher education settings.
The rapid proliferation of artificial intelligence (AI) in higher education has positioned AI literacy as an essential student competency, yet the mechanistic pathways linking this competency to academic outcomes remain insufficiently understood. This study investigates the direct and indirect effects of AI literacy on learning engagement, with a specific focus on the mediating role of psychological capital (PsyCap) and the moderating role of career commitment.Employing a stratified random sampling design, we conducted a cross-sectional questionnaire survey among 1,198 undergraduate students across four universities in Zhengzhou, Henan Province. Path analysis was performed using partial least squares structural equation modeling (PLS‑SEM), and bootstrap resampling was applied to test both mediation and moderated mediation effects.The results reveal that AI literacy exerts a direct, positive influence on learning engagement. Notably, psychological capital partially mediates this relationship, indicating that AI literacy not only directly drives engagement but also indirectly facilitates it by enhancing students' self‑efficacy, hope, optimism, and resilience. Furthermore, career commitment moderates the effect of psychological capital on learning engagement: the indirect effect of AI literacy through psychological capital becomes stronger as students' career commitment intensifies.Collectively, these findings delineate a resource‑transformation pathway-from AI literacy to psychological capital to learning engagement-and identify career commitment as a critical boundary condition. The results carry theoretical implications for understanding the interplay between digital competencies and positive psychological resources, and offer practical guidance for designing educational interventions that synergistically integrate AI training, psychological capital cultivation, and professional identity reinforcement in the era of AI‑enhanced education.