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A Framework for Measuring the Amount of Adaptation of Rasch‐based Computerized Adaptive Tests
Journal of Educational Measurement ( IF 1.4 ) Pub Date : 2020-02-18 , DOI: 10.1111/jedm.12267
Adam E. Wyse 1 , James R. McBride 1
Affiliation  

A key consideration when giving any computerized adaptive test (CAT) is how much adaptation is present when the test is used in practice. This study introduces a new framework to measure the amount of adaptation of Rasch‐based CATs based on looking at the differences between the selected item locations (Rasch item difficulty parameters) of the administered items and target item locations determined from provisional ability estimates at the start of each item. Several new indices based on this framework are introduced and compared to previously suggested measures of adaptation using simulated and real test data. Results from the simulation indicate that some previously suggested indices are not as sensitive to changes in item pool size and the use of constraints as the new indices and may not work as well under different item selection rules. The simulation study and real data example also illustrate the utility of using the new indices to measure adaptation at both a group and individual level. Discussion is provided on how one may use several of the indices to measure adaptation of Rasch‐based CATs in practice.

中文翻译:

用于测量基于Rasch的计算机自适应测试的适应量的框架

进行任何计算机自适应测验(CAT)时,一个关键的考虑因素是在实际使用该测验时存在多少适应性。这项研究引入了一个新的框架,该框架可通过查看管理项目的选定项目位置(Rasch项目难度参数)与从开始时的临时能力估算确定的目标项目位置之间的差异来衡量基于Rasch的CAT的适应量每个项目。引入了基于此框架的几个新指标,并将其与使用模拟和真实测试数据的先前建议的适应性度量进行了比较。模拟的结果表明,某些先前建议的索引对项目库大小的变化和约束的使用不像新索引那样敏感,并且在不同的项目选择规则下可能效果不佳。仿真研究和实际数据示例还说明了使用新指标来衡量群体和个人水平的适应性的实用性。讨论了如何在实践中使用几个指数来衡量基于Rasch的CAT的适应性。
更新日期:2020-02-18
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