Termination Criteria for Computerized Classification Testing.

Q2 Social Sciences
Nathan A. Thompson
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引用次数: 21

Abstract

Computerized classification testing (CCT) is an approach to designing tests with intelligent algorithms, similar to adaptive testing, but specifically designed for the purpose of classifying examinees into categories such as “pass” and “fail.” Like adaptive testing for point estimation of ability, the key component is the termination criterion, namely the algorithm that decides whether to classify the examinee and end the test or to continue and administer another item. This paper applies a newly suggested termination criterion, the generalized likelihood ratio (GLR), to CCT. It also explores the role of the indifference region in the specification of likelihood-ratio based termination criteria, comparing the GLR to the sequential probability ratio test. Results from simulation studies suggest that the GLR is always at least as efficient as existing methods.
计算机分类试验终止标准。
计算机分类考试(CCT)是一种采用智能算法设计考试的方法,类似于自适应考试,但专门设计用于将考生分为“及格”和“不及格”等类别。与能力点估计的自适应测试一样,其关键部分是终止标准,即决定是对考生进行分类并结束测试,还是继续并管理另一个项目的算法。本文将一个新提出的终止准则——广义似然比(GLR)应用于CCT。它还探讨了无差异区域在基于似然比的终止标准规范中的作用,并将GLR与序列概率比检验进行了比较。模拟研究的结果表明,GLR总是至少与现有方法一样有效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
2.60
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