Navigating Teacher Autonomy and Feedback Practices in AI Mediated Iranian EFL Context: A Case Study of Speaking Skill

This study explores how AI tools interact with teachers’ feedback practices and professional autonomy in Iranian EFL classrooms, with a specific focus on speaking skill. Adopting a predominantly qualitative mixed-methods design, the research collected data concurrently through perception questionnaires, semi-structured interviews, and non-participant observations of eight classroom sessions. Eight upper-intermediate EFL instructors from private language institutes in Tehran participated in the study. Quantitative data were analyzed using descriptive statistics, while qualitative data underwent reflexive thematic analysis. The findings reveal that teachers perceive AI both as an augmenter that supports their work and as a potential usurper that may diminish their professional authority. In practice, teachers actively filter and contextualize AI-generated output, a process the study terms “orchestrated feedback.” As a result, teacher autonomy appears to be shifting toward a more dialogic and collaborative form. The study concludes that teacher professional development in the age of AI should move beyond technical training and instead emphasize critical AI-pedagogical literacy. In this evolving landscape, the teacher’s role is transforming from a direct feedback provider into a strategic orchestrator within the learning ecosystem.

کلیدواژه ها:

teacher autonomy ، AI-mediated feedback ، orchestrated feedback ، EFL speaking ، dialogic autonomy