Research on the Application of STEM Practical Teaching Based on RAG Knowledge Graph and Large Models
Jian Lin, Shanyin Mai, Bingqian Bu, Musheng He, Xiaoyi Wang · 2024
Practical experience plays a pivotal role in STEM education, effectively cultivating students' practical skills, innovation capabilities, and critical thinking. However, the scarcity of domain-specific practical experience data within Large Language Models (LLMs) has not fully met the deep-level practical knowledge demands of STEM education, impacting the learners' application outcomes. This paper proposes a STEM practical teaching and inquiry system based on Retrieval-Augmented Generation (RAG) technology and knowledge graphs, aiming to enhance learners' learning experiences and interdisciplinary learning abilities, achieving an intelligent upgrade of STEM practical teaching.