A study on the factors influencing the acceptance of generative artificial intelligence among primary and secondary school teachers

At present, a technological revolution has unfolded in the education sector due to the rapid development of generative artificial intelligence. What makes a profound impact on the quality of educational transformation is whether primary and secondary school teachers are willing to integrate generative artificial intelligence into teaching practices. Against this backdrop, the Unified Theory of Acceptance and Use of Technology (UTAUT) model is applied in this study to investigate the determinants influencing generative artificial intelligence adoption among 448 primary and secondary school teachers. This model incorporates four additional factors: personal innovativeness, self-efficacy, perceived risk, and Technological Pedagogical Content Knowledge (TPACK). It is revealed by this study that personal innovativeness and facilitating conditions have significant positive effects on behavioral intention, while TPACK and behavioral intention exert a significant positive influence on usage behavior. Self-efficacy makes a significant positive impact on TPACK, whereas TPACK exerts a significant negative effect on performance expectancy. Both social influence and TPACK are found to significantly enhance effort expectancy, while social influence, effort expectancy, and self-efficacy are shown to exert significant positive effects on performance expectancy collectively. This study illustrates the moderating role of specific variables. In practice, those teachers with different educational backgrounds vary significantly disparities in performance expectancy, despite the persistent statistical insignificance of other moderating effects. Finally, targeted recommendations are made according to these results to promote the effective integration and development of generative artificial intelligence technology in K-12 educational practices.