多级测试中项目标定方法的研究

IF 0.6 Q3 SOCIAL SCIENCES, INTERDISCIPLINARY
L. Cai, Anthony D. Albano, L. Roussos
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引用次数: 2

摘要

多阶段测试(MST)是一种自适应测试交付模式,它涉及预先定义的项目模块的算法选择,而不是单个项目,提供了线性和完全计算机化的自适应测试的实际替代方案。然而,项目模块和考生群体之间的跨阶段互动可能会导致项目与MST校准的挑战。本研究使用基于操作程序的模拟数据,研究了1-3 MST设计下四种项目校准方法的性能。条件包括路由模块长度、路由规则和样本大小。基于项目和人的参数恢复和分类精度对标定方法进行了评价。结果表明,采用固定的共同项目参数进行标定和采用单一能力分布进行并行标定的效果与采用连接方法进行单独标定和采用多组方法进行并行标定的效果相似。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Investigation of Item Calibration Methods in Multistage Testing
ABSTRACT Multistage testing (MST), an adaptive test delivery mode that involves algorithmic selection of predefined item modules rather than individual items, offers a practical alternative to linear and fully computerized adaptive testing. However, interactions across stages between item modules and examinee groups can lead to challenges in item calibration with MST. This study used simulated data based on an operational program to investigate the performance of four item calibration methods under a 1–3 MST design. Conditions included routing module length, routing rule, and sample size. Calibration methods were evaluated based on item and person parameter recovery and classification accuracy. Results indicated that calibration with fixed common item parameters and concurrent calibration assuming a single ability distribution similarly outperformed both separate calibration with linking and concurrent calibration with the multiple-group procedure.
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来源期刊
Measurement-Interdisciplinary Research and Perspectives
Measurement-Interdisciplinary Research and Perspectives SOCIAL SCIENCES, INTERDISCIPLINARY-
CiteScore
1.80
自引率
0.00%
发文量
23
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