Latent profiles of college students’ AI literacy and their association with AI acceptance: the sequential indirect role of perceived affordances and growth mindset

Abstract

Objective Against the backdrop of the rapid proliferation of generative artificial intelligence (AI), fostering active acceptance and effective utilization of such technologies among college students has emerged as a critical concern in higher education. This study aims to investigate the relationship between AI literacy (AIL) and college students’ AI acceptance (AIA), as well as its underlying mechanisms, while employing latent profile analysis (LPA) to identify heterogeneous types of AIL and examine path differences across distinct latent classes. Methods A sample of 975 Chinese college students completed the AIL Scale, Perceived Affordances (PA) Scale, Growth Mindset (GM) Scale, and AIA Scale. Results AIL exhibited significant positive correlations with PA (r = 0.508, p < 0.001), GM (r = 0.458, p < 0.001), and AIA (r = 0.633, p < 0.001). Mediation analysis revealed that the indirect path via PA accounted for 6.26% of the total association, that of GM for 16.63%, and the chain mediating effect for 4.75%. LPA identified three distinct AIL profiles: low AIL–moderate ethics (26.87%), moderate AIL–low ethics (15.28%), and high-level balanced (57.85%). Notably, the mediating pathways differed across these latent classes, with significant differences observed primarily between the high-level balanced and moderate AIL–low ethics profiles. Conclusion 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.