Teacher responsibility, AI integration, and student well-being: The role of peer collaboration in higher education

This study examines the interaction between teacher responsibility and the integration of artificial intelligence (AI) in learning, and how this influences student mental well-being in higher education, as well as whether peer collaboration amplifies these effects. Guided by ecological systems theory (ecological systems theory), we propose a moderated mediation model where teacher responsibility (microsystem factor) impacts student well-being both directly and indirectly via AI integration (a technological resource in the educational environment), with fellow student collaboration (peer microsystem factor) moderating the pathway. We surveyed 468 university students in four major Chinese cities and analyzed the data using partial least squares structural equation modeling (PLS-SEM). The results indicate that teacher responsibility positively affects student well-being and encourages AI tool integration, which in turn significantly enhances student mental well-being. Furthermore, the positive indirect effect of teacher responsibility on well-being through AI is stronger when peer collaboration is high. This research contributes to theory by linking human, technological, and social dimensions of support in an educational ecology and offers practical insights for leveraging teacher engagement, AI tools, and peer networks to improve student mental health.