{"ID":2884524,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2508.05979","arxiv_id":"2508.05979","title":"Learning by Teaching: Engaging Students as Instructors of Large Language Models in Computer Science Education","abstract":"While Large Language Models (LLMs) are often used as virtual tutors in computer science (CS) education, this approach can foster passive learning and over-reliance. This paper presents a novel pedagogical paradigm that inverts this model: students act as instructors who must teach an LLM to solve problems. To facilitate this, we developed strategies for designing questions with engineered knowledge gaps that only a student can bridge, and we introduce Socrates, a system for deploying this method with minimal overhead. We evaluated our approach in an undergraduate course and found that this active-learning method led to statistically significant improvements in student performance compared to historical cohorts. Our work demonstrates a practical, cost-effective framework for using LLMs to deepen student engagement and mastery.","short_abstract":"While Large Language Models (LLMs) are often used as virtual tutors in computer science (CS) education, this approach can foster passive learning and over-reliance. This paper presents a novel pedagogical paradigm that inverts this model: students act as instructors who must teach an LLM to solve problems. To facilitat...","url_abs":"https://arxiv.org/abs/2508.05979","url_pdf":"https://arxiv.org/pdf/2508.05979v1","authors":"[\"Xinming Yang\",\"Haasil Pujara\",\"Jun Li\"]","published":"2025-08-08T03:25:19Z","proceeding":"cs.CY","tasks":"[\"cs.CY\",\"cs.AI\",\"cs.HC\"]","methods":"[\"Large Language Model\",\"Language Model\"]","has_code":false}