摘要
课程知识图谱是系统整合课程相关知识点和学习资源的有效手段,是人工智能技术赋能课程教学的重要途径,目前已成为在线学习领域的研究热点。以近6年210篇课程知识图谱高质量文献为研究对象,基于隐含狄利克雷分布提取主要研究主题,在此基础上构建课程知识图谱的主要研究内容框架。从理论研究和实践应用两大层面重点总结课程知识图谱的研究现状。在理论研究层面,以知识抽取、知识融合、知识表示及知识推理为主线,对相关研究热点进行深入剖析;在实践应用层面,介绍分析在数智化教材、辅助教学设计、学情分析、智能答疑、个性化学习等五大智能化教学场景的应用,并收集整理各类开放的课程知识图谱数据资源,可用于支持课程知识图谱的相关研究。最后从多粒度多模态知识图谱构建、与大语言模型结合、更广泛深入的智能化课程教学应用等视角展望课程知识图谱的未来发展趋势。
Course knowledge graphs(CKGs)serve as a structured approach to systematically organize course-related knowledge points and learning resources.It plays a crucial role in empowering course teaching with artificial intelligence technology and has become a research focus in the field of online learning.Based on a systematic review of 210 high-quality publications from the last six years,we employ Latent Dirichlet Allocation(LDA)to identify key research themes and establish a comprehensive CKG research framework.We summarize the research status of course knowledge graph from two perspectives:theoretical research and practical applications.Theoretically,we analyze four core research dimensions:(1)knowledge extraction,(2)knowledge fusion,(3)knowledge representation,and(4)knowledge reasoning.Practically,we examine CKGs’implementation across five AI-driven educational scenarios:(1)digital textbooks,(2)instructional design support,(3)learning analytics,(4)intelligent tutoring systems,and(5)personalized learning pathways.We also collect and provide open course knowledge graph data resources,which can be used to support related research.Finally,we outline three future research directions:(1)multi-granularity and multimodal CKG construction,(2)integration with large language models(LLMs),and(3)advanced intelligent teaching applications.
作者
贺超波
杨佳琦
林晓凡
梁卓明
罗辉琼
Chaobo HE;Jiaqi YANG;Xiaofan LIN;Zhuoming LIANG;Huiqiong LUO(School of Computer Science,South China Normal University,Guangzhou 510631,Guangdong;School of Educational Information Technology,South China Normal University,Guangzhou 510631,Guangdong;Network Information Center,South China Normal University,Guangzhou 510631,Guangdong)
出处
《中国教育信息化》
2025年第7期85-96,共12页
Chinese Journal of ICT in Education
基金
2024年国家自然科学基金面上项目“多类型信息融合下生成式聚类增强的课程知识图谱关系预测方法研究”(编号:62477016)
2024年广东省本科高校教学质量与教学改革工程建设项目“课程知识图谱与大语言模型双轮驱动的数智化教材服务模式研究”(编号:粤教高函(2024)30号)。
关键词
课程知识图谱
学习资源
智能化教学
人工智能
在线学习
Course knowledge graph
Learning resources
Intelligent teaching
Artificial intelligence
Online learning
