Cheng Ying, Chang Hua-Hua
Department of Psychology, University of Notre Dame, Notre Dame, USA.
Br J Math Stat Psychol. 2009 May;62(Pt 2):369-83. doi: 10.1348/000711008X304376. Epub 2008 Jun 2.
This paper introduces a new heuristic approach, the maximum priority index (MPI) method, for severely constrained item selection in computerized adaptive testing. Our simulation study shows that it is able to accommodate various non-statistical constraints simultaneously, such as content balancing, exposure control, answer key balancing, and so on. Compared with the weighted deviation modelling method, it leads to fewer constraint violations and better exposure control while maintaining the same level of measurement precision.
本文介绍了一种新的启发式方法——最大优先级指数（MPI）方法，用于计算机化自适应测试中受严格约束的项目选择。我们的模拟研究表明，它能够同时适应各种非统计约束，如内容平衡、曝光控制、答案键平衡等。与加权偏差建模方法相比，它在保持相同测量精度水平的同时，能减少约束违反情况并实现更好的曝光控制。
