Study on Factors Influencing Primary and Secondary School Teachers’ Acceptance of AI Tools Based on the UTAUT Model: A Case Study of Tianchang City, Anhui Province

This study investigates the factors influencing primary and secondary school teachers’ acceptance of artificial intelligence (AI) tools in Tianchang City, Anhui Province, using the Unified Theory of Acceptance and Use of Technology (UTAUT) model. A quantitative approach was employed, with data collected via a structured questionnaire from 300 teachers in Tianchang. The survey measured UTAUT constructs: performance expectancy, effort expectancy, social influence, and facilitating conditions, alongside self-reported AI tool acceptance. Structural equation modeling (SEM) revealed that performance expectancy (β = 0.45, p < .001) and facilitating conditions (β = 0.32, p < .01) were significant predictors of acceptance, whereas effort expectancy (β = 0.18, p = .06) and social influence (β = 0.14, p = .13) showed weaker effects. These findings validate UTAUT’s applicability in explaining AI adoption in educational settings and highlight the critical role of perceived utility and resource accessibility. Regionally, Tianchang teachers’ acceptance aligns with national AI-in-education policies but is shaped by local resource distribution. Practical implications include enhancing technical support, demonstrating AI’s tangible benefits, and tailoring training to reduce effort barriers. This research contributes to understanding technology integration in Chinese K-12 contexts and informs localized strategies for AI implementation.