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用于可复查多维计算机自适应测试的区组项目库方法

The Block Item Pocket Method for Reviewable Multidimensional Computerized Adaptive Testing.

作者信息

Lin Zhe, Chen Ping, Xin Tao

机构信息

Beijing Normal University, China.

出版信息

Appl Psychol Meas. 2021 Jan;45(1):22-36. doi: 10.1177/0146621620947177. Epub 2020 Aug 14.

Abstract

Most computerized adaptive testing (CAT) programs do not allow item review due to a decrease in estimation precision and aberrant manipulation strategies. In this article, a block item pocket (BIP) method that combines the item pocket method with the successive block method to realize reviewable CAT was proposed. A worst-case but still reasonable answering strategy and the Wainer-like manipulation strategy were simulated to evaluate the estimation precision of reviewable unidimensional computerized adaptive testing (UCAT) and multidimensional computerized adaptive testing (MCAT) under a series of BIP settings. For both UCAT and MCAT, it was found that the estimation precision of the BIP method improved as the number of blocks increased or the item pocket size decreased under the reasonable strategy. The BIP method was more effective in handling the Wainer-like strategy. With the help of block design, the BIP method can still maintain acceptable estimation precision under slightly large total IP size conditions. These results suggested that the BIP method was a reliable solution for both reviewable UCAT and MCAT.

摘要

由于估计精度下降和存在异常操纵策略,大多数计算机自适应测试(CAT)程序不允许进行题目回顾。在本文中,提出了一种将题目库方法与连续块方法相结合以实现可回顾CAT的块题目库(BIP)方法。模拟了一种最坏情况但仍合理的答题策略以及类似韦纳的操纵策略,以评估在一系列BIP设置下可回顾单维计算机自适应测试(UCAT)和多维计算机自适应测试(MCAT)的估计精度。对于UCAT和MCAT,发现在合理策略下,随着块数增加或题目库大小减小,BIP方法的估计精度会提高。BIP方法在处理类似韦纳的策略方面更有效。借助块设计,在总题目库大小略大的条件下,BIP方法仍能保持可接受的估计精度。这些结果表明,BIP方法是可回顾UCAT和MCAT的可靠解决方案。

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