Developing IELTS learners’ feedback literacy through AI-assisted self-assessment and revision

Abstract

This conceptual and methodological article examines how IELTS Academic learners can develop feedback literacy when using generative artificial intelligence (AI) for Writing and Speaking practice. It distinguishes receiving an automated suggestion from interpreting its relevance, evaluating its evidence, making a revision decision and checking transfer to a new task. Drawing on established feedback theory, student feedback literacy and formative assessment scholarship, the article proposes a teacher-mediated decision protocol and a transparent revision log. Two illustrative task scenarios demonstrate how learners can compare AI suggestions with IELTS assessment criteria without treating automated comments as official band scores. The contribution is a practical pedagogical framework for cultivating critical engagement with AI feedback, not an experimental claim about score gains. The framework also identifies safeguards concerning learner authorship, privacy, and teacher verification.