基于知识图谱的学习路径自动生成研究  

Research on Automatic Generation of Learning Paths Based on Knowledge Graph

作　　者：高嘉骐 刘千慧 黄文彬[1] GAO Jia-qi;LIU Qian-hui;HUANG Wen-bin(Department of Information Management,Peking University,Beijing,China 100871)

机构地区：[1]北京大学信息管理系,北京100871

出　　处：《现代教育技术》2021年第7期88-96,共9页Modern Educational Technology

摘　　要：海量的学习资源让在线学习者身处"知识迷航"的困境,而人工规划学习路径存在效率较低、难以满足学习者个性化需求的弊端。基于此,文章提出了一种基于知识图谱的学习路径自动生成方法,其将学习路径生成分为知识点路径生成与学习对象路径生成两个步骤,能够根据知识点属性特征及其关系、学习对象属性特征、学习者知识掌握情况与认知特点等对课程中涉及的知识点与学习对象进行序列化。之后,文章通过对照实验检验了此方法的有效性,实验结果表明:采用自动生成路径与专家路径开展学习的被试在学习时间与后测成绩上不存在显著差异;自动生成路径在学习对象的讲解重点与详略设置、局部难易程度设置、整体学习顺序等方面基本符合规范。文章的研究成果可帮助领域专家规划学习路径,为在线学习者提供指导,促进个性化学习。The massive learning resources put online learners in the predicament of“knowledge confusion”,while planning learning paths manually has the disadvantages of low efficiency and difficulty in meeting learners’individual needs.Based on this,the paper proposed an automatic generation method of learning paths based on knowledge graph,which divided the generation of learning paths into two steps of knowledge points path generation and learning objects path generation.Meanwhile,this method can serialize the knowledge points and learning objects involved in the course according to the attribute characteristics and relationships of knowledge points,the attribute characteristics of learning objects,and learners’knowledge mastery situations and cognitive characteristics.Then,the effectiveness of this method was verified through a comparative experiment,and the result showed that there was no significant difference in learning time and post-test scores between the experimenters who adopted the automatic generation path and the expert path.Besides,the automatic generation path basically conformed to the specifications in the aspects of learning objects’interpretation emphases,details and omissions settings,local difficulty and easy degree setting,and overall learning order.The research results of this paper could help domain experts plan learning paths,provide guidance for online learners and promote personalized learning.

关 键 词：学习路径 知识图谱 在线学习 自适应学习 

分 类 号：G40-057[文化科学—教育学原理]