International Journal of Education
International Journal of Education. 2024; 6: (4) ; 10.12208/j.ije.20240082 .
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山东建筑大学外国语学院 山东济南
*通讯作者： 杨丽红,单位：山东建筑大学外国语学院 山东济南；
p-最优化题库设计法是指根据考试目标人群的特点确定符合考试要求的最佳题库蓝图，目的在于确保测试的准确度和题目的均衡利用。p-最优化题库设计法可在题目数量最优化、测量精度最优化和题库设计过程最优化三方面展现其优势。研究发现，此方法可以解决题库题目冗余，试测成本大，测量精度不高等问题，并可简化测量过程。作为低成本、易操作的启发式算法，p-最优化题库设计法的推介旨在为国内计算机自适应考试题库设计和建设提供参考，为命题专家提供试题参数的统计学依据，降低出题成本，提高考试的信度和效度。
The p-optimality method refers to determining the best blueprint of the test item pool that meets the examination requirements based on the characteristics of the target population of the examination. The purpose is to ensure the accuracy of the test and the balanced use of items. This article discusses the advantages of this method from three perspectives: the optimization of the number of items in the pool, the optimization of measurement accuracy, and the optimization of item pool design process. It is discovered that the p-optimality method can address issues such as the redundancy of pool items, reduction of high item trialing costs, and improvement of low measurement precision, simplifying the whole measurement process. As a low-cost and easy-to-operate heuristic algorithm, the promotion of the p-optimality method aims to provide a reference for the design and construction of computerized adaptive testing item pools in China, and provide support for test development experts, reducing the cost of item writing, and improving the reliability and validity of the test.
[1] van der Linden, W. J., Ariel, A., & Veldkamp, B. P. Assembling a CAT item pool as a set of linear tests. Journal of Educational and Behavioral Statistics, 2006, 31, 81-99.
[2] 刘庆思. 英语等级考试题库介绍[J]. 中国考试, 2006 (12): 3-8.
[3] Yang, L., Reckase, M.D. The optimal item pool design in multistage computerized adaptive tests with the p-optimality method. Educational and Psychological Measurement, 2020, 80(5), 955–974.
[4] Liu, Y., Li, Z., Liu, H., & You, X. The Impact of Non-Effortful Responding on Item and Person Parameters in Item-Pool Scaling Linking. Applied Measurement in Education, 2024, 37(2), 89-108.
[5] 杨涛, 杨婷婷, 辛涛. 题库优化设计的回顾与展望[J]. 心理与行为研究, 2012 (3): 154-160.
[6] 修美丽, 柴省三, 鲍杰. 自适性语言测试题库CTT 与IRT参数估计对比研究[J]. 首都师范大学学报(社会科学版) , 2024 (3): 180-189.
[7] Reckase, M. D. Item pool design for computerized adaptive tests. Paper presented at the Annual Meeting of the National Council on Measurement in Education (NCME), Chicago, IL. 2003.
[8] de Ayala, R. J. The theory and practice of item response theory. New York: The Guilford Press. 2009.
[9] Reckase, M. D. Designing item pools to optimize the functioning of a computerized adaptive test. Psychological Test and Assessment Modeling, 2010, 52(2), 127-141.
[10] He, W., & Reckase, M.D. Item pool design for an operational variable-length computerized adaptive test. Educational and Psychological Measurement, 2014, 74(3), 473-494.
[11] Mao, L. Designing p-optimal item pools for multidi-mensional computerized adaptive testing [Unpublished doctoral dissertation]. Michigan State University. 2014.
[12] Zhou, X. Optimal item pool design for computerized adaptive tests with polytomous items using GPCM. Psychological Test and Assessment Modeling, 2014, 56 (3), 255-274.
[13] Gu, L., & Reckase, M. D. Designing optimal item pools for computerized adaptive tests with Sympson-Hetter exposure control. In D. J. Weiss (Ed.), Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing. 2007 .
[14] Reckase, M. D. Multidimensional Item Response Theory. New York: Springer Dordrecht Heidelberg London. 2009.
[15] Pastor, D. A., Dodd, B. G., & Chang, H.H. A comparison of item selection techniques and exposure control mechanisms in CATs using the generalized partial credit model. Applied Psychological Measurement, 2002, 26(2), 147-163.
[16] van der Linden, W. J., Veldkamp, B. P., and Reese, L. M. An integer programming approach to item pool design. Applied Psychological Measurement, 2000, 24(2), 139-150.