Chao Hsiu-Yi, Chen Jyun-Hong
Soochow University, Taiwan.
National Cheng Kung University, Taiwan.
Appl Psychol Meas. 2023 Nov;47(7-8):460-477. doi: 10.1177/01466216231209756. Epub 2023 Oct 20.
Computerized adaptive testing (CAT) can improve test efficiency, but it also causes the problem of unbalanced item usage within a pool. The effect of uneven item exposure rates can not only induce a test security problem due to overexposed items but also raise economic concerns about item pool development due to underexposed items. Therefore, this study proposes a two-stage Sympson-Hetter (TSH) method to enhance balanced item pool utilization by simultaneously controlling the minimum and maximum item exposure rates. The TSH method divides CAT into two stages. While the item exposure rates are controlled above a prespecified level (e.g., ) in the first stage to increase the exposure rates of the underexposed items, they are controlled below another prespecified level (e.g., ) in the second stage to prevent items from overexposure. To reduce the effect on trait estimation, TSH only administers a minimum sufficient number of underexposed items that are generally less discriminating in the first stage of CAT. The simulation study results indicate that the TSH method can effectively improve item pool usage without clearly compromising trait estimation precision in most conditions while maintaining the required level of test security.
计算机自适应测试（CAT）可以提高测试效率，但它也会导致题库中题目使用不均衡的问题。题目曝光率不均衡的影响不仅会因过度曝光的题目引发测试安全问题，还会因曝光不足的题目引发关于题库开发的经济问题。因此，本研究提出一种两阶段的辛普森-赫特（TSH）方法，通过同时控制题目曝光率的最小值和最大值来提高题库的均衡利用率。TSH方法将CAT分为两个阶段。在第一阶段，题目曝光率被控制在预先设定的水平（例如）之上，以提高曝光不足题目的曝光率，而在第二阶段，题目曝光率被控制在另一个预先设定的水平（例如）之下，以防止题目过度曝光。为了减少对特质估计的影响，TSH在CAT的第一阶段只施测数量最少的足够多的曝光不足题目，这些题目通常区分度较低。模拟研究结果表明，TSH方法在大多数情况下可以有效提高题库利用率，同时在保持所需测试安全水平的情况下，不会明显损害特质估计精度。
