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Validity and Reliability of Situational Judgement Test Scores: A New Approach Based on Cognitive Diagnosis Models

机译:情境判断测验分数的有效性和可靠性:一种基于认知诊断模型的新方法

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摘要

Conventional methods for assessing the validity and reliability of situational judgment test (SJT) scores have proven to be inadequate. For example, factor analysis techniques typically lead to nonsensical solutions, and assumptions underlying Cronbach's alpha coefficient are violated due to the multidimensional nature of SJTs. In the current article, we describe how cognitive diagnosis models (CDMs) provide a new approach that not only overcomes these limitations but that also offers extra advantages for scoring and better understanding SJTs. The analysis of the Q-matrix specification, model fit, and model parameter estimates provide a greater wealth of information than traditional procedures do. Our proposal is illustrated using data taken from a 23-item SJT that presents situations about student-related issues. Results show that CDMs are useful tools for scoring tests, like SJTs, in which multiple knowledge, skills, abilities, and other characteristics are required to correctly answer the items. SJT classifications were reliable and significantly related to theoretically relevant variables. We conclude that CDM might help toward the exploration of the nature of the constructs underlying SJT, one of the principal challenges in SJT research.
机译:事实证明,评估情景判断测试(SJT)分数的有效性和可靠性的常规方法是不充分的。例如,因子分析技术通常会导致无意义的解决方案,并且由于SJT的多维性质,违反了Cronbachα系数的假设。在当前的文章中,我们将介绍认知诊断模型(CDM)如何提供一种不仅克服这些局限性的新方法,而且还为评分和更好地理解SJT提供额外的优势。 Q矩阵规范,模型拟合和模型参数估计值的分析提供了比传统过程更多的信息。我们的建议是使用来自23个项目的SJT的数据进行说明的,该数据介绍了与学生相关的问题。结果表明,CDM是评分测试(如SJT)的有用工具,其中需要多种知识,技能,能力和其他特征才能正确回答项目。 SJT分类是可靠的,并且与理论上相关的变量显着相关。我们得出的结论是,CDM可能有助于探索SJT基础结构的性质,这是SJT研究的主要挑战之一。

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