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

机译:关于知识结构表示的模糊逻辑与瞳孔数学概念的应用衡量

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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。通过响应数据和项目概念矩阵,心理模型项目响应理论(IRT)用于校准潜在特征和虚拟逻辑模型的感知(FLMP)是计算概念之间的个性化模糊下级矩阵。从属矩阵上的模糊基础的相似性测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)用于构建个性化知识结构,在概念中显示层次结构和关系。分析了关于学生的公理概念的测试数据,并根据每个学生的相似性值的模糊C-means显示三组。每组显示其知识结构的特定特征。对相似性测量的综合方法和个性化知识结构分析的表示可以提供有用的信息进行补救指导。

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