AI-supported teaching and student engagement: the mediating role of perceived competence in vocational education
Introduction Artificial intelligence (AI) is increasingly used in education, yet less is known about the psychological processes through which AI-supported teaching relates to student engagement, especially in vocational education. Drawing on Self-Determination Theory, this study examined the mediating roles of perceived competence and perceived autonomy in the relationship between AI-supported teaching and student engagement. Methods A 10-week quasi-experimental study was conducted with 148 second-year vocational college students, assigned to either an AI-supported teaching group (n = 74) or a conventional instruction group (n = 74). Multimodal data were collected, including academic assessments, performance evaluations, self-report measures of perceived competence, perceived autonomy, and engagement, as well as behavioral records from AI-supported learning activities. Mediation analysis was performed using bootstrapping with 5,000 resamples. Results Students in the AI-supported teaching group showed higher levels of student engagement than those in the conventional instruction group (Cohen's d = 0.84). Perceived competence showed a statistically significant indirect association between AI-supported teaching and student engagement [β = 0.22, 95% CI (0.13, 0.31)], supporting H2. In contrast, perceived autonomy did not show a statistically significant indirect effect [β = 0.02, 95% CI (−0.02, 0.06)], and therefore H3 was not supported. The direct association between AI-supported teaching and engagement remained significant after accounting for both mediators. Discussion These findings suggest that competence-related experiences may represent an important psychological pathway linking AI-supported teaching and student engagement in structured vocational education contexts. The non-significant role of perceived autonomy indicates that motivational processes in AI-supported learning may vary across instructional settings and should be interpreted in relation to contextual and pedagogical conditions. Given the quasi-experimental design and the context-specific sample, the findings should be interpreted cautiously and further examined through larger, multi-site, andlongitudinal studies.