AI technostress and professional identity among Chinese university teachers: the mediating role of teaching self-efficacy and the moderating role of perceived organizational support

Abstract

Generative artificial intelligence (AI) has entered university teaching faster than the evidence needed to guide its use, and teachers carry much of the resulting strain. This study examined whether AI technostress is associated with the professional identity of university teachers through teaching self-efficacy, and whether perceived organizational support buffers this pathway. A cross-sectional questionnaire survey was conducted with a convenience sample of 486 full-time teachers from five public universities in Guangxi, China, all of whom had used at least one generative AI tool in their teaching or course preparation. Respondents completed Chinese adaptations of established measures of AI technostress, teaching self-efficacy, professional identity, and perceived organizational support. The measurement properties of the adapted scales were verified with confirmatory factor analysis and competing-model comparisons, and the hypotheses were tested with a moderated mediation path analysis based on 5,000 bootstrap resamples. AI technostress was negatively associated with professional identity, and teaching self-efficacy partially accounted for this association. Perceived organizational support moderated the first link of the pathway: the negative association between AI technostress and teaching self-efficacy was weaker among teachers who perceived stronger institutional backing, and the indirect association with professional identity was correspondingly smaller. These findings suggest that teachers’ professional identity is vulnerable to technology-related strain and that institutional support may attenuate this vulnerability. Universities that invest in efficacy-oriented professional development and visible organizational support are better positioned to help teachers sustain their professional identity as generative AI becomes embedded in teaching.