Pre-Service Teachers’ Behavioral Intentions Toward AI Integration : An Extension of the Technology Acceptance Model

Artificial Intelligence (AI) has the potential to significantly enhance English language instruction and learning in classrooms. Despite the growing interest in AI in education, little is known about pre-service teachers’ intentions to adopt AI in their future classrooms. This study examined the behavioral intention of pre-service English as a foreign language teachers (PSEFLTs) to use AI to enhance English instruction and learning in their future classrooms. By examining factors such as AI anxiety, perceived utility, perceived ease of use, AI self-efficacy, AI literacy, and AI readiness, this study extends the Technology Acceptance Model (TAM), serves as a theoretical framework, to better understand PSEFLTs' intentions to adopt AI. A structured survey was administered to 100 PSEFLTs across three different Iranian Teacher Education Universities. Using partial least squares-structural equation modeling (PLS-SEM). The results showed that PSEFLTs' behavioral intentions to adopt AI are positively influenced by AI self-efficacy, perceived usefulness, perceived ease of use, AI literacy, and AI readiness. while, AI anxiety was a negative predictor, underscoring the psychological obstacles to the adoption of technology. These results highlight how important it is for teacher education programs to promote AI literacy, lower anxiety, and boost self-efficacy in order to guarantee successful AI integration. By extending TAM and tackling the understudied topic of PSTs' adoption of AI technologies, the study adds to the body of literature.