A study on the acceptance of generative artificial intelligence and its influencing mechanisms among pre-service international Chinese language teachers based on the UTAUT model

With the rapid development of artificial intelligence, generative AI has increasingly influenced global language education. However, empirical research on the acceptance of generative artificial intelligence by pre-service international Chinese language teachers is limited. This study sought to investigate the acceptance and influencing mechanisms of generative artificial intelligence among pre-service international Chinese language teachers. Qualitative research methods, including semi-structured interviews and focus group discussions, were employed, and the Unified Theory of Acceptance and Use of Technology model was used for analysis. The study revealed that pre-service international Chinese language teachers generally recognised the pedagogical value of generative AI, viewing it as a tool to enhance teaching efficiency. However, they also identified practical concerns such as students’ over-reliance on the technology, detachment from cultural context, and potential intellectual property risks. Performance expectancy, effort expectancy, social influence, and facilitating conditions all influenced teachers’ willingness to use generative artificial intelligence, with performance expectancy having the most significant positive impact. At the same time, technical limitations, insufficient training, and unclear policies were found to be significant barriers that reduced teachers’ acceptance intention. Ultimately, pre-service international Chinese language teachers exhibited a dual-track acceptance attitude, balancing instrumental rationality with humanistic considerations. The findings provided empirical support for the integration of generative artificial intelligence into international Chinese language education