用户生成性学习资源知识顺序自动识别方法

计算机科学 ›› 2019, Vol. 46 ›› Issue (6A): 598-600.

用户生成性学习资源知识顺序自动识别方法

肖奎¹, 陈志雄¹, 刘国君¹, 黄志芳²

湖北大学计算机与信息工程学院武汉430062¹;
湖北大学教育学院武汉430062²

出版日期:2019-06-14 发布日期:2019-07-02
通讯作者: 肖奎(1981-),男,博士,副教授,主要研究方向为知识管理、众包模式与数据挖掘,E-mail:xiaokui1024@hotmail.com
作者简介:陈志雄(1983-),男,硕士,实验师,主要研究方向为软件工程;刘国君(1978-),男,硕士,高级实验师,主要研究方向为信息管理;黄志芳(1982-),女,博士,讲师,主要研究方向为适应性学习路径推荐、数字化学习资源建设。
基金资助:
本文受全国教育科学“十二五”规划2015年度教育部青年课题:基于网络教学资源组合的课程个性化定制方法研究(ECA150374)资助。

Approach for Discovering Prerequisite Relationships Between User Generated Learning Resources

XIAO Kui¹, CHEN Zhi-xiong¹, LIU Guo-jun¹, HUANG Zhi-fang²

School of Computer Science and Information Engineering,Hubei University,Wuhan 430062,China¹;
School of Education,Hubei University,Wuhan 430062,China²

Online:2019-06-14 Published:2019-07-02

摘要/Abstract

摘要： 近年来,随着互联网的普及,用户生成性学习资源的数量快速增长。文中以维基百科为例,提出了一种用户生成性学习资源知识顺序自动识别方法,分别从词条所属分类层次、词条链接关系、词条长度等方面判断两个相关对象的学习顺序。实验结果表明,所提方法能够为相关对象的学习顺序判定提供有效的支持。

关键词: 课程构建, 维基百科, 学习对象排序, 用户生成性学习资源, 知识顺序

Abstract: In recent years,the number of user generated learning resources grew rapidly along with the popularity of the Internet.This paper proposed an approach for discovering prerequisite relationships between user generated learning resources based on Wikipedia.The relationships between related learning resources are find out by Wikipedia categories,article links,as well as article length.The experiment results show that these properties are useful for sequencing lear-ning resources.

Key words: Course building, Learning objects sequencing, Prerequisite relationship, User generated learning resource, Wikipedia

中图分类号:

TP391.1

肖奎, 陈志雄, 刘国君, 黄志芳. 用户生成性学习资源知识顺序自动识别方法[J]. 计算机科学, 2019, 46(6A): 598-600. https://doi.org/

XIAO Kui, CHEN Zhi-xiong, LIU Guo-jun, HUANG Zhi-fang. Approach for Discovering Prerequisite Relationships Between User Generated Learning Resources[J]. Computer Science, 2019, 46(6A): 598-600. https://doi.org/

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