Diao Qi, Ren Hao
ACT, Inc., Monterey, CA, USA.
Appl Psychol Meas. 2018 Oct;42(7):538-552. doi: 10.1177/0146621617753736. Epub 2018 Feb 20.
Imposing content constraints is very important in most operational computerized adaptive testing (CAT) programs in educational measurement. Shadow test approach to CAT (Shadow CAT) offers an elegant solution to imposing statistical and nonstatistical constraints by projecting future consequences of item selection. The original form of Shadow CAT presumes fixed test lengths. The goal of the current study was to extend Shadow CAT to tests under variable-length termination conditions and evaluate its performance relative to other content balancing approaches. The study demonstrated the feasibility of constructing Shadow CAT with variable test lengths and in operational CAT programs. The results indicated the superiority of the approach compared with other content balancing methods.
在教育测量中，施加内容约束在大多数操作性计算机自适应测试（CAT）程序中非常重要。CAT的影子测试方法（影子CAT）通过预测项目选择的未来结果，为施加统计和非统计约束提供了一个优雅的解决方案。影子CAT的原始形式假定测试长度固定。本研究的目标是将影子CAT扩展到可变长度终止条件下的测试，并评估其相对于其他内容平衡方法的性能。该研究证明了构建具有可变测试长度的影子CAT以及在操作性CAT程序中的可行性。结果表明，该方法优于其他内容平衡方法。
