As artificial intelligence (AI) becomes more deeply integrated into higher education, understanding its effects on student creativity has become increasingly important. However, the mechanisms through which AI use is associated with student creativity, as well as the boundary conditions of this relationship, remain insufficiently understood. Drawing on the knowledge-based dynamic capabilities (KBDC) framework, this study develops and tests a model that links AI use to student creativity while incorporating the moderating roles of AI self-efficacy and AI trust. Using survey data from 764 university students in China, we employ hierarchical regression analysis to examine the proposed model. The results show that AI use is positively associated with student creativity and that this relationship is mediated by students' knowledge acquisition, absorptive, and combination capabilities.
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