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在计算机化适应性测试中选择项目的最大标准

Jyun-Hong Chen¹, Hsiu-Yi Chao²

¹Department of Psychology, National Cheng Kung University, No. 1, University Road, Tainan City, 701401, Taiwan.

Behavior research methods

|May 28, 2025

概括

根据MaxiMin信息 (MMI) 标准,通过平衡项目池利用,提高计算机自适应测试 (CAT). 这种新方法提高了测试效率和安全性,特别是在高风险的评估中.

科学领域:

心理测量心理测量心理测量
教育测量教育的测量
计算机化的适应性测试 (CAT)

背景情况:

在CAT中,基于信息的项目选择规则 (ISR),与最大费舍尔信息 (MFI) 一样,经常过度利用高度歧视性的项目.
这导致项目池使用不平衡,并可能导致测试安全问题.

研究的目的:

介绍和评估MaxiMin信息 (MMI) 在CAT中的项目选择标准.
评估MMI在保持特征估计精度的同时平衡项目池利用的能力.

主要方法:

开发了基于决策理论的MMI标准,选择具有特征水平当前置信区间 (CI) 中最大最小信息的项目.
在各种条件下进行了五项模拟研究,以比较MMI与其他ISR.

主要成果:

MMI的特征估计准确度与现有的ISR相比较.
MMI显著改善了项目池利用平衡.
MMI根据特征估计精度调整了项目选择,为更广泛的CI选择了不那么有歧视性的项目,为更狭窄的CI选择了更有歧视性的项目.

结论:

由于其平衡的项目池利用率和效率,MMI是CAT的一个有希望的ISR,特别是在高风险测试中.
建议使用MMI,以95%的置信度为最佳性能.
MMI为提高CAT效率和安全提供了一个实用的解决方案.

关键词:

计算机化的适应性测试决策理论决策理论项目选择规则项目选择规则最多信息的标准是最大的信息.最多的费舍尔信息

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