Beyond Answers: Large Language Model-Powered Tutoring System in Physics Education for Deep Learning and Precise Understanding

This paper presents Physics-STAR, an LLM-powered tutoring system for high school physics education, and evaluates it through a controlled experiment with 12 sophomore students, comparing it against traditional teacher-led lectures and generic LLM tutoring. The study measures learning outcomes (conceptual, computational, and informational problem scores) and efficiency, finding significant improvements especially on complex information problems (100% score increase, 5.95% efficiency gain).

The integration of artificial intelligence (AI) in education has shown significant promise, yet the effective personalization of learning, particularly in physics education, remains a challenge. This paper proposes Physics-STAR, a framework for large language model (LLM)- powered tutoring system designed to address this gap by providing personalized and adaptive learning experiences for high school students. Our study evaluates Physics-STAR against traditional teacher-led lectures and generic LL

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