AI anxiety and AI learning intention among Chinese university students: a protection motivation theory perspective

The rapid development of artificial intelligence (AI) has introduced new psychological and educational challenges for university students. In higher education settings, students may perceive AI as a source of employment pressure, skill renewal demands, and future uncertainty, while also regarding AI learning as an important form of academic and career preparation. Drawing on Protection Motivation Theory (PMT), this study examines the associations among perceived threat severity, perceived threat vulnerability, response efficacy, self-efficacy, AI anxiety, protection motivation, and AI learning intention among Chinese university students. Based on cross-sectional survey data from 350 undergraduates in mainland China, structural equation modeling (SEM) was used to test the proposed relationships, and fuzzy-set qualitative comparative analysis (fsQCA) was further used to identify configurations associated with high AI learning intention. The SEM results indicated good model fit, χ2/df = 1.629, RMSEA = 0.042, TLI = 0.948, CFI = 0.952, and IFI = 0.952. Perceived threat severity and perceived threat vulnerability were positively associated with both AI anxiety and protection motivation. Self-efficacy and AI anxiety were positively associated with protection motivation, whereas response efficacy showed a positive but statistically non-significant direct association with protection motivation. Protection motivation was positively associated with AI learning intention. The mediation results suggested small but statistically significant indirect associations between threat perceptions and protection motivation through AI anxiety. The fsQCA results complemented the SEM findings by identifying multiple configurations associated with high AI learning intention, including an efficacy-motivation configuration, a threat-motivation configuration, and an anxiety-efficacy configuration. These findings suggest that AI learning intention among Chinese university students is associated with the joint presence of threat appraisal, efficacy beliefs, AI anxiety, and protection motivation rather than any single psychological factor. This study contributes incremental evidence to AI learning research by clarifying how cognitive, emotional, and motivational factors are related within a PMT-based framework.