Making sense of AI feedback: how students’ feedback literacy moderates the link between ChatGPT acceptance and self-regulated learning

Abstract

The integration of generative AI tools like ChatGPT in education raises fundamental questions about boundary conditions where students perceive such technologies as beneficial. This study examines whether students’ feedback literacy capabilities determine their perceived educational value from AI interactions. Drawing on the Technology Acceptance Model, we surveyed 211 secondary students (grades 7–9) regarding their ChatGPT acceptance, feedback sense-making abilities, and self-reflection. Hierarchical regression analyses revealed that while technology acceptance components were positively associated with self-reflection, these relationships were consistently moderated by feedback literacy. Specifically, students with stronger feedback sense-making abilities reported greater benefits from ChatGPT use, while those with weaker sense-making skills showed minimal or negative associations. These findings position feedback literacy as a crucial condition influencing perceived educational utility of GenAI tools. The results challenge assumptions about the broad-spectrum or universal benefits of GenAI adoption and highlight the need for targeted and feedback literacy development among learners.