EFL Teachers' Acceptance of Generative Artificial Intelligence in Teaching and Academic Research: Use Experience as Moderator

Abstract

Generative Artificial Intelligence (GAI) technology, represented by large language models, has driven an in-depth transformation of foreign language education and research. In the era of digital intelligence, how digital technology empowers English as a Foreign Language (EFL) teaching and academic research is a new topic for foreign language educators. This research adopts the integration of UTAUT theory to predict the influence of GAI on EFL teachers' teaching and academic research by conceptualising the EFL teachers' teaching and academic research model (ETTAR Model). The inner relationship within the ETTAR Model was examined using analytical software—Smart PLS 4.0. A five-point Likert online questionnaire on ETTAR was distributed among 132 teachers who teach English at foreign language colleges across seven northern Chinese higher educational institutions. The research results indicated that social influence, performance expectancy, effort expectancy and facilitating conditions positively influence teachers' behavioural intentions to use GAI in EFL teaching and research. Moreover, experience had a positive moderating effect on social influence and the behavioural intentions of EFL teachers utilising GAI. This research further confirmed that EFL teachers' teaching with GAI significantly positively impacts their academic research powered by GAI.