IRT-based scoring methods for multidimensional forced choice tests

Subjects: Psychology >> Psychological Measurement submitted time 2021-12-14

刘娟 郑蝉金 李云川 连旭

Abstract： Forced-choice (FC) test is widely used in non-cognitive tests because it can control the response bias caused by the traditional Likert method, while traditional scoring of forced-choice test produces ipsative data that has been criticized for being unsuitable for inter-individual comparisons. In recent years, the development of multiple forced-choice IRT models that allow researchers to obtain normative information from forced-choice test has re-ignited the interest of researchers and practitioners in forced-choice IRT models. First, the six prevailing forced-choice IRT models are classified and introduced according to the adopted decision models and item response models. Then, the models are compared and summarized from two perspectives: model construction ideology and parameter estimation methods. Next, it reviews the applied research of the model in three aspects: parameter invariance testing, computerized adaptive testing (CAT) and validity study. Finally, it is suggested that future research can move forward in four directions: model expansion, parameter invariance testing, forced-choice CAT, and validity research. "

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