作　　者： ;

机构地区： 湖南商学院信息学院

出　　处： 《计算机仿真》 2010年第3期302-305,共4页

摘　　要： 针对知识库是教学系统的核心,是实现系统智能化的关键。为了提高网络教学系统的决策和诊断能力,满足自适应学习的需要,设计了一个基于层次结构的语义网络和产生式的二级知识表示模型,提出了广度优先的知识点剪枝算法和深度优先的知识点遍历算法,对所学习知识点进行选取及对相应的知识网络遍历,并通过采用知识点学习的智能导航算法仿真学生在系统中自适应学习的全过程。实验结果表明,知识模型的设计有助于实现网络教学资源动态组织和教学策略的动态调整,能够更好地为学生提供个性化的学习参考需要,为系统决策分析提供参考依据。 Knowledge base is the core of education system and the key to realize the system intellectualization. In order to improve the personalization service level in network edncation system and satisfiy the need of adaptive learning, this article designed a model of two stage knowledge expressions by semantic network and production rule based on hierarchical structure. A pruning algorithm based on breadth priority search of knowledge points and a knowledge traversal algorithm based on depth priority search of knowledge points were proposed, in order to select the knowledge points and traversal for the corresponding knowledge network graph. And based on this, the entire process of adaptive learning in system was simulated by designing intelligence guidance algorithm of knowledge learning. The experimental result indicates that this knowledge representation model is helpful in the dynamic organization of network teaching resources and the dynamic adjustment of teaching strategy. This model can provide personalized study recommendation for students, and provide the intelligent auxiliary foundation for the system decision and analysis.

关 键 词： 网络教学系统 知识表示模型 搜索策略 自适应学习

领　　域： [文化科学] [文化科学]