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Fuzzy Logic on Representation of Knowledge Structure and Measure of Similarity with Application on Mathematics Concepts for Pupils

机译:知识结构表示和相似性度量的模糊逻辑及其在小学生数学概念中的应用

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The purpose of this study is to investigate the knowledge structure representation based on fuzzy theory. With response data and item-concept matrix, the psychometric model item response theory (IRT) is used to calibrate latent trait and fuzzy logic model of perception (FLMP) is to calculate individualized fuzzy subordinate matrix among concepts. Similarity measurement of fuzzy basis on the subordinate matrix provides the comparisons between knowledge structures of each student and the expert. Fuzzy structural modeling (FSM) is used to construct the individualized knowledge structures which display hierarchies and relationship among concepts. A testing data set on axiom concepts for pupils is analyzed and it displays three groups according to fuzzy c-means on similarity values of each student. Each group displays its specific characteristics of knowledge structure. The integrated methodology on similarity measurement and representation of individualized knowledge structure analysis could provide helpful information for remedial instruction.
机译:本研究的目的是研究基于模糊理论的知识结构表示。借助响应数据和项目概念矩阵,使用心理测量模型项目响应理论(IRT)来校准潜在特征,而感知的模糊逻辑模型(FLMP)则用于计算概念之间的个性化模糊从属矩阵。在下属矩阵上的模糊基础相似度度量提供了每个学生和专家的知识结构之间的比较。模糊结构建模(FSM)用于构建个性化的知识结构,这些知识结构显示层次结构和概念之间的关系。分析了针对学生的公理概念的测试数据集,并根据每个学生的相似度值的模糊c均值显示了三组。每个小组展示其知识结构的特定特征。相似性度量和个性化知识结构分析表示的集成方法可以为辅导教学提供有用的信息。

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