{"slug": "towards-just-in-time-adaptive-feedback-enhancing-student-learning-via-knowledge", "title": "Towards Just-in-Time Adaptive Feedback: Enhancing Student Learning via Knowledge-Grounded LLM", "summary": "Researchers have developed a framework that uses large language models to deliver just-in-time adaptive feedback to students by grounding the AI with domain-specific expert knowledge. Deployed in a university course with over 1,000 students, the system improved student performance by more than 80% compared to previous semesters. The framework analyzes students' written reasoning to identify errors and provides non-intrusive feedback, with iterative LLM conversations helping shift misconceptions toward correct understanding.", "body_md": "arXiv:2605.26405v1 Announce Type: new\nAbstract: Educational interventions are effective tools for enhancing student learning. While Large Language Models (LLMs) allow for generating adaptive feedback at scale, current studies lack clear methodologies for providing Just-in-Time (JiT) feedback in authentic instructional settings. In this paper, we present a framework that provides adaptive feedback by grounding LLMs with domain-specific expert knowledge. Our approach collects written reasoning logic (strategy essays) from students, analyzes potential error types based on the content of that reasoning, and delivers non-intrusive feedback designed to clarify missing or incorrect concepts. We deploy this framework in a large-scale university course (N > 1000), where it improved student performance by over 80% compared to previous semesters. Lastly, we validate the framework's pedagogical utility by analyzing the learning trajectories; we demonstrate how iterative conversations with LLM facilitate shifting one's misconception to correct understanding.", "url": "https://wpnews.pro/news/towards-just-in-time-adaptive-feedback-enhancing-student-learning-via-knowledge", "canonical_source": "https://arxiv.org/abs/2605.26405", "published_at": "2026-05-27 04:00:00+00:00", "updated_at": "2026-05-27 04:34:44.962298+00:00", "lang": "en", "topics": ["large-language-models", "artificial-intelligence", "natural-language-processing", "ai-ethics", "ai-research"], "entities": ["Large Language Models", "LLM"], "alternates": {"html": "https://wpnews.pro/news/towards-just-in-time-adaptive-feedback-enhancing-student-learning-via-knowledge", "markdown": "https://wpnews.pro/news/towards-just-in-time-adaptive-feedback-enhancing-student-learning-via-knowledge.md", "text": "https://wpnews.pro/news/towards-just-in-time-adaptive-feedback-enhancing-student-learning-via-knowledge.txt", "jsonld": "https://wpnews.pro/news/towards-just-in-time-adaptive-feedback-enhancing-student-learning-via-knowledge.jsonld"}}