Computerized Adaptive Testing Method Using Integer Programming to Minimize Item Exposure

Computerized Adaptive Testing Method Using Integer Programming to Minimize Item Exposure
复制标题

使用整数规划最小化项目暴露的计算机化自适应测试方法

DOI:
10.1007/978-3-030-39878-1_10
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发表时间:
2020
期刊:
Advances in Artificial Intelligence: Selected Papers from the Annual Conference of Japanese Society of Artificial Intelligence
影响因子:
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通讯作者:
Maomi Ueno
Maomi Ueno
中科院分区:
--
文献类型:
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作者:
Yoshimitsu Miyazawa;Maomi Ueno

文献摘要

相似文献

这是从JSAI2019中选择的论文的扩展。计算机化自适应测试(CAT)依次估计被测者的能力,并选择具有最高准确度的测试项目来估计能力。然而,常规CAT为具有同等能力的考生选择相同的项目。如本文所述,我们提出CAT,最大限度地减少项目曝光,并自适应地选择不同的项目,为考生的同等能力,同时保持准确性。本文通过仿真数据和实际测试数据验证了该方法的有效性。
This is an extension from a selected paper from JSAI2019. Computerized adaptive testing (CAT) estimates an examinee’s ability sequentially and selects test items that have the highest accuracy for estimating the ability. However, conventional CAT selects the same items for examinees who have equivalent ability. As described herein, we propose CAT that minimizes item exposure and which adaptively selects different items for examinees of equal ability, while retaining accuracy. This paper presents the method’s effectiveness using simulation data and actual test data.