From Familiarity to Criticality: Cultivating EFL Teachers’ AI Literacy Through an AI-Integrated Genre-Based Pedagogy

Although AI integration in education is accelerating, professional development for Chinese EFL teachers remains predominantly techno-centric and lacks disciplinary specificity, resulting in persistently lower levels of AI literacy. To address this, this study used an eight-week AI-Integrated Genre-Based Pedagogy (AI-GBP) module grounded in Situated Learning Theory and TPACK. A quasi-experimental, explanatory, sequential, and mixed-methods design was employed to compare the AI-GBP module with a generic AI-literacy program among 64 Chinese college EFL teachers (n = 32 per group). Quantitative data from pre- and post-intervention surveys were analyzed using ANCOVA and MANCOVA to determine differences, while qualitative data from semi-structured interviews underwent thematic analysis. Quantitative findings indicated statistically significant gains in overall AI literacy as well as in its subcomponents, particularly regarding practical application and critical appraisal, among teachers in the AI-GBP group compared with the control group. Qualitative findings revealed certain developmental shift from tool-oriented AI use toward more critical and pedagogically relevant engagement, including teachers’ increased ability to identify model bias, contextual mismatch, and ‘agreeableness’ AI possesses. These findings suggest that embedding AI learning within more pedagogically and contextually appropriate situations (e.g., genre-based pedagogy) can support EFL teachers’ sustainable and critical integration and understanding of AI in their professional practice.