具有混合格式项目的双因子多维计算机自适应测试的优化设计。

IF 1 4区 心理学 Q4 PSYCHOLOGY, MATHEMATICAL
Applied Psychological Measurement Pub Date : 2022-10-01 Epub Date: 2022-06-14 DOI:10.1177/01466216221108382
Xiuzhen Mao, Jiahui Zhang, Tao Xin
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引用次数: 1

摘要

使用混合格式项目的多维计算机自适应测试(MCAT)在下一代评估中具有巨大的潜力。在混合格式双因子MCAT的背景下,讨论了混合格式测试设计中的两个关键因素(即多角形项目的顺序和比例)和项目选择。对于项目选择,本文推导了双因子分级响应模型的Fisher信息矩阵,并应用双因子降维方法简化了互信息(MI)项目选择方法的计算。在一项模拟研究中,将不同的MCAT设计与不同比例的多面体项目(0.2-0.6,1)、不同的项目交付格式(DPmix:在最后阶段交付多面体项目;RPmix:随机交付)、三种双因素模式(低、中、高)和两种项目选择方法(贝叶斯D-最优性和MI)进行了比较。仿真结果表明:a)双因子模式越高,整体估计精度越高;b) 两种项目选择方法在估计精度上没有显著差异;以及c)RPmix格式总是导致比DPmix格式更精确的中期和最终估计。建议RPmix和DPmix格式分别使用0.3和0.4的比例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Optimal Design of Bifactor Multidimensional Computerized Adaptive Testing with Mixed-format Items.

Multidimensional computerized adaptive testing (MCAT) using mixed-format items holds great potential for the next-generation assessments. Two critical factors in the mixed-format test design (i.e., the order and proportion of polytomous items) and item selection were addressed in the context of mixed-format bifactor MCAT. For item selection, this article presents the derivation of the Fisher information matrix of the bifactor graded response model and the application of the bifactor dimension reduction method to simplify the computation of the mutual information (MI) item selection method. In a simulation study, different MCAT designs were compared with varying proportions of polytomous items (0.2-0.6, 1), different item-delivering formats (DPmix: delivering polytomous items at the final stage; RPmix: random delivering), three bifactor patterns (low, middle, and high), and two item selection methods (Bayesian D-optimality and MI). Simulation results suggested that a) the overall estimation precision increased with a higher bifactor pattern; b) the two item selection methods did not show substantial differences in estimation precision; and c) the RPmix format always led to more precise interim and final estimates than the DPmix format. The proportions of 0.3 and 0.4 were recommended for the RPmix and DPmix formats, respectively.

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来源期刊
CiteScore
2.30
自引率
8.30%
发文量
50
期刊介绍: Applied Psychological Measurement publishes empirical research on the application of techniques of psychological measurement to substantive problems in all areas of psychology and related disciplines.
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