基于认知诊断的CAT概念格构建算法

Xiaojing Liu, Wenbing Wu, Fei Yu, Deng Chang
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引用次数: 0

摘要

概念格的构造在形式概念分析中起着重要的作用。目前,认知诊断是研究人员关注的焦点,计算机自适应测试(computer Adaptive Testing, CAT)的认知诊断具有广阔的发展前景,但相关研究较少。形式概念分析(Form Concept Analysis, FCA)可以应用于CAT,从理论上讲,CAT的概念格可以作为具有认知诊断的CAT考生的学习模型。考虑属性层次,给出并详细讨论了CAT概念格的构造算法,并从理论上证明了该算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Algorithms of Constructing Concept Lattices Based On CAT With Cognitive Diagnosis
Constructing concept lattices plays an important role in Formal Concept Analysis. At present, cognitive diagnosis is a focus for researchers, and Computerized Adaptive Testing (CAT) with cognitive diagnosis is prospected but there are few relevant researches. Form Concept Analysis(FCA) can be applied into CAT, and the concept lattices for CAT are theoretically served as a learning model for examinees in CAT with cognitive diagnosis. Considering the attribute hierarchy, the algorithm of constructing concept lattices for CAT is given and discussed in detail, which is proved theoretically.
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