Developing Teacher Feedback Literacy in AI Enhanced Assessment: Evidence from Pre Service English Teachers

Feedback, long seen as central to learning, has traditionally been teacher-controlled, corrective, and one-way, positioning students as passive, grade-focused recipients. Contemporary perspectives, however, reconceptualise feedback as a dialogic, socially mediated process grounded in shared responsibility and co-constructed meaning. The rise of Generative AI (GenAI) tools such as ChatGPT has further transformed feedback and assessment by enabling internal feedback, multimodal scaffolding, and greater learner agency, while also introducing pedagogical and ethical challenges. Yet, progress toward dialogic and AI-informed feedback remains limited by insufficient feedback literacy among teachers and students. Although student feedback literacy has gained attention, research on teacher development, especially within AI-mediated assessment and initial teacher education remains scarce.
This study addresses the gap by exploring feedback literacy development among 18 English pre-service teachers during their practicum. Using classroom observations, interviews, and reflective journals, the analysis reveals noticeable shifts from summative and judgmental feedback toward formative, multimodal, and dialogic approaches including peer, self, and GenAI-supported feedback. Findings underscore the value of practicum-based learning in preparing teachers for ethical, human-centred feedback practices in AI-enhanced assessment settings.