基于知识图谱的《线性代数》课程建设研究

Research on the Construction of Linear Algebra Course Based on Knowledge Graph

摘要: 随着高等工程教育对知识体系化与智能化教学的需求日益增强，传统《线性代数》课程在知识组织和教学实践中存在知识碎片化、概念关联弱化及学习路径单一等问题。本文提出基于知识图谱的课程建设方法，构建了覆盖数据采集、知识建模、语义关联与智能应用的系统框架，并设计了知识点层、概念层、应用层与能力层的四层课程知识图谱模型，实现课程知识、理论概念、工程应用及学生能力的多维映射与动态关联。同时，开展教学资源重组与智能学习设计，支持个性化学习路径推荐、知识掌握度诊断及智能教学干预。研究表明，知识图谱驱动的课程建设可提升课程体系结构化水平。

Abstract: As higher engineering education increasingly demands systematic knowledge organization and intelligent teaching approaches, traditional Linear Algebra courses face challenges such as fragmented knowledge, weakened conceptual connections, and limited learning pathways in both knowledge organization and teaching practices. This paper proposes a knowledge graph-based course development methodology, establishing a systematic framework encompassing data collection, knowledge modeling, semantic association, and intelligent applications. A four-layer course knowledge graph model—comprising knowledge points, concepts, applications, and competencies—is designed to achieve multidimensional mapping and dynamic linkage among course knowledge, theoretical concepts, engineering applications, and student competencies. Building upon this foundation, teaching resources are reorganized and intelligent learning designs are implemented to support personalized learning path recommendations, knowledge mastery diagnostics, and intelligent teaching interventions. Research indicates that knowledge graph-driven curriculum development enhances the structural integrity of course systems.