AI acceptance and Chinese EFL learners’ behavioral engagement with mediating effects of motivation

As artificial intelligence (AI) technologies become increasingly integrated into education, understanding how they influence learners' engagement is essential for effective pedagogy. This study examines the motivational mechanisms by which Chinese EFL learners' acceptance of AI tools influences their behavioral engagement. Grounded in Self-Determination Theory and the Unified Theory of Acceptance and Use of Technology, a cross-sectional survey was conducted among 654 university students. Structural equation modeling revealed that AI acceptance positively predicted motivation (β = 0.628, p < .001), which in turn significantly predicted engagement (β = 0.517, p < .001). A direct effect of AI acceptance on engagement (β = 0.253, p < .001) was also observed. Bootstrap mediation analysis revealed significant indirect effects of AI acceptance on behavioral engagement, particularly via self-satisfaction and self-efficacy. These findings highlight the importance of fostering autonomous motivation to translate positive perceptions of AI into active learning behaviors. The study provides empirical support for the integration of learner-centered AI and suggests that motivationally supportive design and pedagogy are crucial for maximizing AI's educational potential.