Explanatory Item Response Models for Polytomous Item Responses

Authors : Luke STANKE, Okan BULUT

Pages : 259-278

Doi:10.21449/ijate.515085

View : 13 | Download : 4

Publication Date : 2019-07-15

Article Type : Research Paper

Abstract :Item response theory is a widely used framework for the design, scoring, and scaling of measurement instruments. Item response models are typically used for dichotomously scored questions that have only two score points insert ignore into journalissuearticles values(e.g., multiple-choice items);. However, given the increasing use of instruments that include questions with multiple response categories, such as surveys, questionnaires, and psychological scales, polytomous item response models are becoming more utilized in education and psychology. This study aims to demonstrate the application of explanatory item response models to polytomous item responses in order to explain common variability in item clusters, person groups, and interactions between item clusters and person groups. Explanatory forms of several polytomous item response models – such as Partial Credit Model and Rating Scale Model – are demonstrated and the estimation procedures of these models are explained. Findings of this study suggest that explanatory item response models can be more robust and parsimonious than traditional item response models for polytomous data where items and persons share common characteristics. Explanatory polytomous item response models can provide more information about response patterns in item responses by estimating fewer item parameters.
Keywords : Polytomous IRT, Explanatory item response modeling, Assessment, Partial Credit Model