From Critical Thinking Disposition to Learning Engagement: The Roles of Motivation, Academic Buoyancy, and Grit in AI ‐Supported University Learning

ABSTRACT Artificial intelligence is changing university students' learning experiences, but how cognitive dispositions translate into sustained engagement in AI‐supported learning remains insufficiently understood. Guided by the Study Demands–Resources Model, this study examines the association between critical thinking disposition and learning engagement, with learning motivation, academic buoyancy, and grit as parallel indirect pathways. Using cross‐sectional data from 729 university students with experience using AI for learning, structural equation modelling tested the direct and indirect relationships among the variables, after which psychological network analysis identified central and bridge nodes within the learning psychological system. Critical thinking disposition was conceptualised as a cognitive personal resource, and learning motivation as a motivational resource. Academic buoyancy captured students' capacity to manage everyday academic setbacks, whereas grit represented perseverance in pursuing long‐term learning goals. The combination of variable‐centred and network‐based analyses provided complementary views of how these resources relate to university students' engagement in AI‐supported learning.