What drives students to learn with GenAI? A dual-pathway model of cognitive and socio-affective mechanisms

This study proposes and empirically tests a dual-pathway integrative model to explain the psychological mechanisms underlying Chinese undergraduate students’ adoption and use of GenAI for learning. Combining cognitive appraisal theory, task-technology fit and socio-affective factors, the model examines how cognitive-utility and socio-affective pathways shape students’ appraisals, emotions, and behavioral intentions. Data from 794 students were analyzed using PLS-SEM. Results show that the cognitive-utility pathway, particularly task-technology fit, strongly predicts challenge appraisal and behavioral intention, while socio-affective factors exert more nuanced effects. Challenge and hindrance appraisals directly influence intention, with positive emotion mediating the former. Gender moderated only one socio-affective path, while academic discipline showed no significant moderation. The study contributes to theoretical integration in technology adoption and provides guidance for educators on effectively integrating GenAI in higher education.