个性化学习空间优化及路径推荐研究  

Research on the optimization of personalized learning space and learning path recommendation

作　　者：王蓉 李小青[2] 刘军兰[1] 严晓梅[2] 陈瑜 WANG Rong;LI Xiao-qing;LIU Jun-lan;YAN Xiao-mei;CHEN Yu(College of Engineering,Xi’an International University,Xi’an 710077,China;Information and Navigation College,Airforce Engineering University,Xi’an 710077,China;Unit 95866 of People's Liberation Army,Baoding 071000,China)

机构地区：[1]西安外事学院工学院,陕西西安710077 [2]空军工程大学信息与导航学院,陕西西安710077 [3]中国人民解放军95866部队,河北保定071000

出　　处：《电子设计工程》2020年第12期6-11,16,共7页Electronic Design Engineering

基　　金：国家自然科学基金青年科学基金项目(71503260);陕西省创新能力支撑计划项目(2019KRM123)。

摘　　要：为提供个性化学习空间,优化在线学习效果,文章介绍了一种基于领域本体和语义相似度的个性化学习路径推荐策略。首先对根据领域知识点及其关系构建本体库,建立其知识点间语义层面的关系,并用Protégé进行了本体形式化编码;然后基于本体,设计了学习路径生成策略和相关知识协同策略;最后,结合决策支持系统课程现有网络资源设计并开发了原型系统,实现了个性化学习引导及资源空间的优化。This paper introduces a recommendation strategy of personalized learning path based on domain ontology and semantic similarity,in order to provide personalized learning space and optimize the effect of online learning.Firstly,according to the domain knowledge and their relations,the ontology database is found to construct the relationship of knowledge pointsat the semantic level.In addition,the ontology is formally encoded using the Protégé.Then,it designs the learning path generation strategy and the related knowledge cooperation strategy.After that the prototype system is designed and developed based on the existing resources of the decision support system online course.The experiment results show thatthe personalized learning guidance and resource space is optimized.

关 键 词：资源空间优化 学习路径推荐 领域本体 语义相似度 原型系统 个性化学习引导 

分 类 号：TN915[电子电信—通信与信息系统]