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

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.