DeCarlo Lawrence T
Teachers College, Columbia University, New York, NY, USA.
Educ Psychol Meas. 2024 Dec;84(6):1076-1106. doi: 10.1177/00131644241235333. Epub 2024 Mar 28.
A psychological framework for different types of items commonly used with mixed-format exams is proposed. A choice model based on signal detection theory (SDT) is used for multiple-choice (MC) items, whereas an item response theory (IRT) model is used for open-ended (OE) items. The SDT and IRT models are shown to share a common conceptualization in terms of latent states of "know/don't know" at the examinee level. This in turn suggests a way to join or "fuse" the models-through the probability of knowing. A general model that fuses the SDT choice model, for MC items, with a generalized sequential logit model, for OE items, is introduced. Fitting SDT and IRT models simultaneously allows one to examine possible differences in psychological processes across the different types of items, to examine the effects of covariates in both models simultaneously, to allow for relations among the model parameters, and likely offers potential estimation benefits. The utility of the approach is illustrated with MC and OE items from large-scale international exams.
本文提出了一个适用于混合格式考试中常用的不同类型试题的心理框架。基于信号检测理论（SDT）的选择模型用于多项选择题（MC），而项目反应理论（IRT）模型用于开放式（OE）试题。研究表明，SDT和IRT模型在考生层面的“知道/不知道”潜在状态方面具有共同的概念化。这反过来又提出了一种通过知道的概率来连接或“融合”模型的方法。引入了一个通用模型，该模型将用于MC试题的SDT选择模型与用于OE试题的广义顺序逻辑模型相融合。同时拟合SDT和IRT模型可以让人们检验不同类型试题在心理过程上可能存在的差异，同时检验两个模型中协变量的影响，考虑模型参数之间的关系，并且可能带来潜在的估计优势。通过大规模国际考试中的MC和OE试题说明了该方法的实用性。
