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A comparison of computer-based classification testing approaches using mixed-format tests with the generalized partial credit model.

机译:使用混合格式测试和广义部分信用模型的基于计算机的分类测试方法的比较。

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摘要

Classification testing has been widely used to make categorical decisions by determining whether an examinee has a certain degree of ability required by established standards. As computer technologies have developed, classification testing has become more computerized. Several approaches have been proposed and investigated in the context of computer-based classification testing, including: (1) Computerized adaptive test (CAT) (2) Multistage test (MST) (3) Sequential probability ratio test (SPRT), among others.The purpose of this study was to systematically compare the differences in classification decision precision among several testing approaches (i.e., CAT, MST, and SPRT) given three test lengths and three cutoff scores using mixed-format tests based on the generalized partial credit model. The progressive-restricted exposure control procedure and constrained CAT content balancing procedure with test unit types were also incorporated as part of this study. All conditions were evaluated in terms of the classification decision precision and the exposure control property.Overall, this study's results indicated that all three approaches performed well in terms of classifying people into two categories. The CAT and SPRT approaches produced, on average, comparable results with both performing relatively better than the MST approach in the precision of their classification decision. As the test length increased, the classification decision accuracy generally increased for all approaches however, the CAT and SPRT approaches yielded more accuracy with the shorter test length. In terms of cutoff scores, predicting classification decision differed according to the location of cutoff scores based on the normal distribution of examinees.In terms of exposure control properties, the progressive-restricted exposure control procedure with the pre-set maximum test unit exposure rate was implemented effectively into the CAT and SPRT approaches. The CAT approach had, on average, a higher proportion of test units with low test unit exposure rates and produced better results in pool utilization rates than the SPRT approach. Finally, the MST approach administered all test units constructed for the panels for each condition. It had, on average, however, a higher proportion of test units with high test unit exposure rates because computations were based only on the proportion of whole test unit pool used for constructing the MST panels.
机译:分类测试已广泛用于通过确定应试者是否具有既定标准所需的一定程度的能力来做出分类决策。随着计算机技术的发展,分类测试变得更加计算机化。已经提出了几种基于计算机的分类测试方法,并进行了研究,包括:(1)计算机自适应测试(CAT)(2)多阶段测试(MST)(3)顺序概率比测试(SPRT)等。这项研究的目的是系统地比较几种测试方法(即CAT,MST和SPRT)在给定三个测试长度和三个截止分数的情况下的分类决策精度的差异,这些方法使用基于广义部分信用模型的混合格式测试。逐步限制的暴露控制程序和带有测试单元类型的受约束的CAT含量平衡程序也作为本研究的一部分。总体而言,本研究结果表明,在将人分为两类方面,所有三种方法均表现良好。平均而言,CAT和SPRT方法产生的结果可比,两者在分类决策的精度上均比MST方法更好。随着测试长度的增加,所有方法的分类决策准确性通常都会提高,但是CAT和SPRT方法在较短的测试长度下产生了更高的准确性。就截止分数而言,根据应试者的正态分布,根据截止分数的位置来预测分类决策是不同的。就暴露控制特性而言,采用预先设定的最大测试单位暴露率的逐步限制暴露控制程序是有效地实施到CAT和SPRT方法中。与SPRT方法相比,CAT方法平均具有较高的测试单元比例,且测试单元的暴露率较低,并且池利用率更高。最后,MST方法管理了针对每种条件为面板构建的所有测试单元。但是,平均而言,具有较高测试单元暴露率的测试单元比例较高,因为计算仅基于用于构建MST面板的整个测试单元池的比例。

著录项

  • 作者

    Kim, Jiseon.;

  • 作者单位

    The University of Texas at Austin.;

  • 授予单位 The University of Texas at Austin.;
  • 学科 Education Tests and Measurements.Education Educational Psychology.Psychology Psychometrics.
  • 学位 Ph.D.
  • 年度 2010
  • 页码 181 p.
  • 总页数 181
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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