REFINE: Real-world Exploration of Interactive Feedback and Student Behaviour

ArXi:2603.29142v1 Announce Type: new Formative feedback is central to effective learning, yet providing timely, individualised feedback at scale remains a persistent challenge. While recent work has explored the use of large language models (LLMs) to automate feedback, most existing systems still conceptualise feedback as a static, one-way artifact, offering limited for interpretation, clarification, or follow-up. In this work, we