物理化学知识图谱的构建及其在自主学习中的应用

Construction of Physical Chemistry Knowledge Graph and Its Application in Self-Directed Learning

摘要: 知识图谱为教育领域带来了革命性的变革，它可视化表达了知识结构，帮助学习者规划个性化学习路径，有望推动教育智能化与个性化发展。本文讨论了利用知识分类、知识提取、知识表示、知识关联、整合与优化等步骤构建得到物理化学知识图谱。物理化学知识图谱能够为自主学习者呈现一个学科领域的完整知识结构。自主学习者可以根据自己的学习目标和现有知识水平，利用知识图谱规划学习路径，同时对学习进度进行监测，对学习效果进行评价。此外知识图谱可以帮助学习者发现知识点之间的潜在联系，拓展知识的广度和深度，深入思考将物理化学的基础知识进行灵活应用。

Abstract: The knowledge graph has brought revolutionary changes to the field of education. Graph visualization expresses the knowledge structure and helps learners plan personalized learning paths, which is expected to promote the intelligent and personalized development of education. This article discusses the construction of a physical chemistry knowledge graph using steps such as knowledge classification, knowledge extraction, knowledge representation, knowledge association, integration, and optimization. The knowledge graph of physical chemistry can present a complete knowledge structure of a subject area to autonomous learners. Autonomous learners can use knowledge graphs to plan their learning paths based on their learning goals and existing knowledge levels, while monitoring their learning progress and evaluating their learning outcomes. In addition, knowledge graphs can help learners discover potential connections between knowledge points, expand the breadth and depth of knowledge, and think deeply about flexibly applying the basic knowledge of physics and chemistry.