Heterogeneity in AI readiness and its influence on behavioral intentions to use AI: a comparison between pre-service and in-service foreign language teachers

Adopting a comparative perspective between pre-service and in-service teachers, this study investigated the potential heterogeneity underlying foreign language (FL) teachers' artificial intelligence (AI) readiness and its influence on their behavioral intention to use AI. Data were collected from 492 pre-service and 533 in-service FL teachers through an online survey. The results revealed significantly higher levels of AI readiness and behavioral intention among pre-service teachers compared to their in-service counterparts. A person-centered approach through latent profile analysis (LPA) identified three AI readiness profiles among pre-service teachers and four AI readiness profiles among in-service teachers, with the majority of both groups demonstrating a moderate level of AI readiness. Multigroup partial least squares structural equation modeling (PLS-SEM) supported the predictive role of AI readiness on behavioral intention to use AI for both teacher groups. Significant differences were also observed between the two groups regarding the predictive effects of AI-technological pedagogical and content knowledge (TPACK) and institutional support on behavioral intention. The findings provide insights into fostering AI readiness through tailored teacher education to support effective AI integration in FL education.