基于“人工智能 + 知识图谱”的大学物理数智课程建设与实践

Construction and Practice of a Digital-Intelligent University Physics Course Based on “AI + Knowledge Graph”

摘要: 随着人工智能(AI)技术的发展，高等教育数字化转型受到广泛关注。本文针对大学物理课程教学中存在的知识碎片化、个性化学习支持不足、教学反馈滞后等问题，提出了基于“人工智能 + 知识图谱”的大学物理数智课程建设方案。通过构建大学物理知识图谱、开发AI智能体，建立“师/生/机”三元互动教学模式，并在某高校工科专业开展两个学期的教学实践。实践结果表明，该模式在提升学生学习效果、促进个性化学习、支持教师调整教学策略等方面展现出积极效果，为同类课程的数智化转型提供了实践思路与参考案例。

Abstract: The digital transformation of higher education has drawn increasing attention with the advancement of artificial intelligence. University physics teaching often faces challenges such as fragmented knowledge, limited personalized learning support, and delayed feedback. This study proposes a digital-intelligent course construction approach based on “AI + Knowledge Graph”. A university physics knowledge graph was constructed, an AI agent was developed, and a triadic interactive teaching model involving teachers, students, and machines was implemented in an engineering program over two semesters. The findings suggest that the model has positive effects on students’ learning outcomes, personalized learning, and teachers’ instructional decision-making. The study offers practical insights and a reference case for the digital-intelligent transformation of similar courses.