知识图谱是人工智能技术赋能现代教育的重要途径，课程知识图谱将教学内容拆解和系统梳理，构建知识点之间的相互关系并优化知识表达，对课程建设和人才培养具有划时代的意义. 本文以2023年出版的《理工科类大学物理课程教学基本要求》为依据构建了大学物理课程图谱，设计提出并实践了三种问题牵引式教学策略，完成了课程知识图谱的教学探索，能够为新工科视域下的数智化数理基础课程建设提供有益启示.

Knowledge graph (KG) is an important way to empower modern education using artificial intellicollege physics|digitization|online and offline blended teaching mode gence (AI) technology. A curriculum knowledge graph (CKG) can systematically reorganize teaching content, construct the interrelationships between knowledge points. As a result, it can optimize knowledge expression and make significance for curriculum construction and talent cultivation. This article constructs a CKG based on the “Basic Requirements for Teaching Physics Courses in Science and Engineering Universities” published in 2023. Three problemoriented teaching strategies are designed, and implemented towards the future application of CKG. It can provide useful inspiration for the Digitalization and Intelligence of the fundamental mathematics and physics courses in the Emerging Engineering Education (3E) perspective.