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Polytomous IRS with Application in Concepts Diagnosis and Clustering on Fraction Subtraction for Pupils

机译:多组织IRS应用于概念诊断和聚类对瞳孔的馏分减法

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The purpose of this study is to provide the polytomous item relational structure (PIRS) analysis and utilize it in fraction subtraction concepts diagnosis with classification on pupils by fuzzy clustering. Beyond the limitations of dichotomous item relational structure (IRS), PIRS is well efficient in the analysis of polytomous data. Most IRS application aims to analyze item hierarchies, not concept hierarchies. However, hierarchies of conceptual attributes will be meaningful for pedagogy and PIRS could provide graphical concept hierarchies according to response data matrix and item-concept matrix. PIRS analysis based on results of clustering on subjects would be more effective for remedial instruction. In this study, empirical data of fraction subtraction testing for sixth graders will be analyzed by fuzzy clustering and PIRS is applied to display concept hierarchies for each group. The results show that the integration of PIRS and fuzzy clustering are feasible for cognition diagnosis and remedial instruction. Finally, some suggestions and recommendations are discussed.
机译:本研究的目的是提供多种物品关系结构(PIRS)分析,并在零件减法概念诊断中使用模糊聚类对学生进行分类。超出二分项关系结构(IRS)的局限性,PIR在​​多元素数据的分析中有效。大多数IRS应用程序旨在分析项目层次结构,而不是概念层次结构。但是,概念属性的层次结构对于教育学,PIR可以根据响应数据矩阵和项目概念矩阵提供图形概念层次结构。基于聚类结果的PIRS分析对受试者的结果将更有效地对补救说明。在这项研究中,将通过模糊聚类分析第六分级机的分数减法测试的经验数据,并应用PIR来显示每个组的概念层次结构。结果表明,PIR和模糊聚类的整合对于认知诊断和补救指导是可行的。最后,讨论了一些建议和建议。

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