Teaching With AI , Engaging With Purpose: University Teachers' Work Engagement in AI ‐Supported Higher Education
TL;DR
Findings extend the JD‐R model to AI‐supported higher education and highlight the importance of institutional support, AI literacy development, and psychological resource building in enhancing teachers' engagement.
Abstract
Artificial intelligence (AI) is increasingly reshaping higher education, requiring university teachers to adapt their pedagogical roles, technological competence, and professional engagement. Drawing on the Job Demands–Resources (JD‐R) model, this study examined how organizational support and AI literacy were associated with university teachers' work engagement in AI‐supported teaching, with professional identity, resilience, and self‐efficacy as mediating personal resources. A questionnaire survey was conducted among 1135 Chinese university teachers with experience in AI‐supported teaching. Data were analysed using structural equation modelling (SEM), mediation analysis, and network analysis. SEM results showed that organizational support and AI literacy were positively associated with professional identity, resilience, and self‐efficacy, which were further positively associated with work engagement. Mediation analysis indicated that professional identity, resilience, and self‐efficacy mediated the relationships between organizational support, AI literacy, and work engagement. Network analysis further revealed that work engagement was the most central node, with self‐efficacy showing the strongest connection with engagement. These findings extend the JD‐R model to AI‐supported higher education and highlight the importance of institutional support, AI literacy development, and psychological resource building in enhancing teachers' engagement.