Developing pre-service language teachers’ GenAI literacy: an interventional study in an English language teacher education course - Ting Huang; Chenze Wu; Meixin Wu (Discover Artificial Intelligence)
Abstract Generative Artificial Intelligence (GenAI) tools are transforming the field of language education. Recent studies indicated that English language teachers generally lacked the readiness and skills necessary to effectively and critically integrate these tools into their professional practices. This study employed a mixed-method interventional design to investigate the impact of integrating GenAI tools into a 12-week training course on the development of pre-service English language teachers’ GenAI literacy. 90 pre-service language teachers enrolled in a B.A. in English program at a university in southeastern China were recruited. The participants were divided into an experimental group (n = 45) and a control group (n = 45). Data was collected through a mixed-methods questionnaire and analyzed using Analysis of Covariance (ANCOVA) and thematic analysis. The results demonstrated a significant improvement in the experimental group’s overall GenAI literacy and its five sub-dimensions following the 12-week intervention. The experimental group significantly outperformed the control group in the post-test, as evidenced by their GenAI literacy across all five sub-dimensions (overall GenAI literacy, p < 0.001; technical proficiency, p < 0.001; critical evaluation, p < 0.001; communication proficiency, p < 0.05; creative application, p < 0.001; ethical competence, p < 0.001). This study provides valuable insights for school leaders and program directors to integrate explicit GenAI literacy training into language teacher education programs. It emphasizes the necessity for language educators to engage in ongoing professional development focused on GenAI, ensuring that they stay updated with the latest GenAI advancements and their applications in language education.