Knowledge Building Theory (KB) and its teaching platform Knowledge Forum (KF) are representative knowledge innovation learning theories and technologies in the international learning science community,representing the direction of change in teaching and learning in the 21st century. From the perspective of theoretical research and practical needs,a bottleneck in knowledge building research is that in the process of continuous knowledge building,community members have formed a large number of unstructured and semi-structured data fragments on the KF platform.The KF platform can only do shallow visual representation,and it is difficult to analyze the depth of its structure.This research focuses on the key issues of automatic construction of knowledge structure in knowledge building.It tries to construct knowledge model technology such as natural language processing, semantic analysis and entity relationship discovery by constructing the theoretical model between human-activity-knowledge.Therefore,the scheme of the knowledge map construction engine is designed,and then the path of the actual application of model is revealed in combination with the practical teaching process.%知识建构理论(KB)及其技术环境知识论坛(KF)是当今国际学习科学界具有代表性的知识创新学习理论与技术,代表着21世纪"教与学"的变革方向.从理论研究与实践需求看,知识建构研究的一个瓶颈问题是在持续的知识建构过程中,社区成员在KF平台里形成了海量的"非结构化""半结构化"数据碎片,KF平台目前只能做浅层次的可视化表达,而难以对其进行结构化的深度分析.本研究围绕知识建构学习社区知识图谱自动构建的关键问题,力图通过建构"人—活动—知识"之间的理论模型,提出借助自然语言处理、语义分析、实体关系发现等知识图谱技术,研发知识图谱构建引擎的方案,进而结合教学实践过程,展示实际应用的路径.
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