针对地方高校大学物理课程中学生基础差异大、教学模式同质化、知识碎片化及学用脱节等突出问题，教学团队依托在线平台，重构了“课前导学-课程核心-知识拓展-思政融入-专业衔接”五位一体的线上教学资源体系，并遵循知识关联性与认知规律构建了大学物理知识图谱。通过融合人工智能与知识图谱技术，实施个性化学习路径推荐与精准化学情诊断，实现了“师-生-机”深度协同的混合式教学。实践表明，该模式有效提升了学生的学习效果，为地方高校基础课程的智慧化教学提供了可借鉴的实践范式。

In response to the prominent problems such as large differences in students' basic foundation, homogeneous teaching modes, fragmented knowledge, and disconnection between learning and application in college physics courses of local universities, the teaching team reconstructed a five-in-one online teaching resource system of "pre-class guidance-core course content-knowledge expansion-ideological and political integration-professional connection" based on an online platform, and constructed a college physics knowledge graph in accordance with the knowledge relevance and cognitive laws. By integrating Artificial intelligence(AI) and knowledge graph technology, personalized learning path recommendation and precise learning situation diagnosis were implemented, and a deeply collaborative blended teaching mode of "teacher-student-machine" was realized. Practice results show that this model has effectively improved students' learning effects, and provided a practical paradigm for the intelligent teaching of basic courses in local universities.