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首页> 外文期刊>Educational and Psychological Measurement >Polytomous adaptive classification testing: Effects of item pool size, test termination criterion, and number of cutscores
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Polytomous adaptive classification testing: Effects of item pool size, test termination criterion, and number of cutscores

机译：多态自适应分类测试：项目库大小，测试终止条件和得分的影响

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摘要

Computer-adaptive classification tests focus on classifying respondents in different proficiency groups (e.g., for pass/fail decisions). To date, adaptive classification testing has been dominated by research on dichotomous response formats and classifications in two groups. This article extends this line of research to polytomous classification tests for two- and three-group scenarios (e.g., inferior, mediocre, and superior proficiencies). Results of two simulation experiments with generated and real responses (N = 2,000) to established personality scales of different length (12, 20, or 29 items) demonstrate that adaptive item presentations significantly reduce the number of items required to make such classification decisions while maintaining a consistent classification accuracy. Furthermore, the simulations highlight the importance of the selected test termination criterion, which has a significant impact on the average test length.
机译：计算机自适应分类测试的重点是对不同能力组中的受访者进行分类（例如，通过/不通过决定）。迄今为止，自适应分类测试已被对二分类响应格式和两组分类的研究所主导。本文将这一研究范围扩展到针对两组和三组方案的多分类分类测试（例如，较低，中等和较高的熟练度）。对已建立的不同长度（12、20或29个项目）的人格量表进行实际反应（N = 2,000）的两个模拟实验的结果表明，自适应项目显示可显着减少做出此类分类决策所需的项目数量，同时保持一致的分类精度。此外，仿真突出显示了所选测试终止标准的重要性，这对平均测试长度具有重大影响。

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