AI technology has become increasingly integral to higher education, yet its impact on teachers remains critically understudied. Drawing on STARA Theory and Resource Conservation Theory, this study unpacks the genesis, influencing factors, and mechanism of teacher burnout triggered by AI awareness among university educators. A total of 326 questionnaires were administered to in-service teachers across China’s eastern, central, and western regions, encompassing 985/211 universities, public/private undergraduate institutions, and vocational colleges, via Wenjuanxing, a leading Chinese survey platform. After rigorous screening, 312 valid responses were retained (95.7% validity rate). The study employed 5-point Likert scales — adapted from validated instruments — to measure AI awareness (4 items) 1, organizational self-esteem (4 items) 2, perceived organizational support (4 items) 3, and teacher burnout (3 items) 4. SPSS analyses included descriptive statistics, reliability tests (Cronbach’s Formula: see text), variance inflation factor (VIF) checks (all Formula: see text), Pearson correlations, and hierarchical regression modeling to test direct effects, the mediating role of organizational self-esteem, and the moderating role of organizational support. Results reveal that AI technology adoption significantly induces AI awareness among teachers, which exacerbates teaching-related burnout. Organizational self-esteem partially mediates this relationship, as AI awareness-driven depletion of psychological resources influences burnout likelihood via reduced perceived professional value. Additionally, organizational support significantly moderates the AI awareness–burnout link, underscoring the critical role of institutional resources in buffering negative effects. Notably, these findings align with non-Asian studies 5, 6, suggesting cross-cultural validity of the AI awareness–burnout pathway and its implications for global educational contexts where AI integration is accelerating. This research highlights the need to address AI-induced professional challenges, offering actionable strategies for educational administrators to support faculty in AI-integrated environments, mitigate burnout risks, and foster sustainable pedagogical ecosystems.
Zhang et al. (Tue,) studied this question.
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