混合格式考试的融合 SDT/IRT 模型

IF 2.1 3区 心理学 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Lawrence T. DeCarlo
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引用次数: 0

摘要

针对混合形式考试中常用的不同类型的题目,提出了一个心理学框架。基于信号检测理论(SDT)的选择模型适用于多项选择(MC)题目,而项目反应理论(IRT)模型则适用于开放式(OE)题目。结果表明,SDT 模型和 IRT 模型在被试者水平上的 "知道/不知道 "潜在状态方面具有共同的概念。这反过来又提出了一种通过 "知道 "的概率来连接或 "融合 "这两种模型的方法。本文介绍了一个通用模型,该模型融合了针对 MC 项目的 SDT 选择模型和针对 OE 项目的广义顺序 logit 模型。同时拟合 SDT 模型和 IRT 模型,可以考察不同类型项目的心理过程可能存在的差异,同时考察两个模型中协变量的影响,考虑模型参数之间的关系,并可能带来潜在的估算优势。我们用大型国际考试中的 MC 和 OE 项目来说明这种方法的实用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fused SDT/IRT Models for Mixed-Format Exams
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.
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来源期刊
Educational and Psychological Measurement
Educational and Psychological Measurement 医学-数学跨学科应用
CiteScore
5.50
自引率
7.40%
发文量
49
审稿时长
6-12 weeks
期刊介绍: Educational and Psychological Measurement (EPM) publishes referred scholarly work from all academic disciplines interested in the study of measurement theory, problems, and issues. Theoretical articles address new developments and techniques, and applied articles deal with innovation applications.
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