Lesson study as an approach to facilitate the integration of Gen-AI into EFL curriculum design in higher education

Purpose This study investigates how English as a Foreign Language (EFL) teachers from higher education develop and refine their curriculum design with Generative Artificial Intelligence (Gen-AI) collaboration during the Lesson Study (LS). Design/methodology/approach Through a qualitative case study approach, we followed six English teachers in their collaborative work with a Gen-AI teaching assistant (Kimi) over a 6-month semester. Data were collected through the recordings of LS cycles, teacher interviews and reflections and documentation of teacher-AI interactions etc. Findings The findings revealed three key aspects of Gen-AI integration in designing EFL curriculum: First, teachers progressively discovered Kimi’s capabilities in lesson planning, material development, and activity design, showing value in generating differentiated learning resources. Second, the teachers developed sophisticated collaboration patterns with the Gen-AI, demonstrating iterative refinement approaches and strategic integration of Gen-AI suggestions throughout the LS cycles. Third, teachers' critical reflections showed evolution in their evaluation and application of Gen-AI contributions, maintaining professional agency while leveraging Gen-AI capabilities effectively. Research limitations/implications This study has several limitations that inform future research directions. Our investigation focused specifically on EFL higher education using a single Gen-AI tool (Kimi), which may limit the generalizability of the findings to other educational contexts and AI platforms. Practical implications These findings suggest that Gen-AI integration through LS can enhance teachers' professional practice while promoting critical engagement with Gen-AI tools. The study provides insights into how Gen-AI can be meaningfully integrated into teacher professional development through collaborative LS approaches. Originality/value The study demonstrates how the LS framework supports balanced AI integration while maintaining teacher agency. In addition, it reveals the process of AI capability discovery and strategic implementation in EFL teaching.