Nie Lei, Xu Peiyi, Hu Di
School of Public Administration, East China Normal University, China.
Department of Educational Psychology, Faculty of Education, East China Normal University, China.
Heliyon. 2024 Feb 22;10(5):e26884. doi: 10.1016/j.heliyon.2024.e26884. eCollection 2024 Mar 15.
The Multidimensional Forced Choice (MFC) test is frequently utilized in non-cognitive evaluations because of its effectiveness in reducing response bias commonly associated with the conventional Likert scale. Nonetheless, it is critical to recognize that the MFC test generates ipsative data, a type of measurement that has been criticized due to its limited applicability for comparing individuals. Multidimensional item response theory (MIRT) models have recently sparked renewed interest among academics and professionals. This is largely due to the development of several models that make it easier to collect normative data from forced-choice tests. The paper introduces a modeling framework made up of three key components: response format, measurement model, and decision theory. Under this paradigm, four IRT models were chosen as examples. Following that, a comprehensive study is carried out to compare and characterize the parameter estimation techniques used in MFC-IRT models. This work then examines empirical research on the concept by analyzing three distinct domains: parameter invariance testing, computerized adaptive testing (CAT), and validity investigation. Finally, it is recommended that future research initiatives follow four distinct paths: modeling, parameter invariance testing, forced-choice CAT, and validity studies.
多维强制选择（MFC）测试因其在减少通常与传统李克特量表相关的反应偏差方面的有效性，而经常用于非认知评估。然而，必须认识到，MFC测试产生的是自比性数据，这种测量类型因其在比较个体方面的适用性有限而受到批评。多维项目反应理论（MIRT）模型最近在学术界和专业人士中重新引起了兴趣。这主要归功于几个模型的发展，这些模型使从强制选择测试中收集常模数据变得更加容易。本文介绍了一个由三个关键部分组成的建模框架：反应格式、测量模型和决策理论。在此范式下，选择了四个IRT模型作为示例。随后，进行了一项全面研究，以比较和描述MFC-IRT模型中使用的参数估计技术。这项工作接着通过分析三个不同领域来检验关于该概念的实证研究：参数不变性测试、计算机自适应测试（CAT）和效度调查。最后，建议未来的研究计划遵循四条不同的路径：建模、参数不变性测试、强制选择CAT和效度研究。
