Explanatory Item Response Models for Polytomous Item Responses
| Autor: | Okan Bulut, Luke Stanke |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Polytomous item
partial credit model assessment Ocean Engineering Polytomous IRT explanatory item response modeling assessment partial credit model behavioral disciplines and activities lcsh:Education (General) explanatory item response modeling 0504 sociology Rating scale model Item response theory Econometrics Education Scientific Disciplines Estimation 05 social sciences 050401 social sciences methods 050301 education Polytomous Rasch model Eğitim Bilimsel Disiplinler Polytomous IRT Explanatory item responsemodeling Assessment Partial Credit Model Multiple response Psychology polytomous irt lcsh:L lcsh:L7-991 0503 education lcsh:Education |
| Zdroj: | International Journal of Assessment Tools in Education, Vol 6, Iss 2, Pp 259-278 (2019) Volume: 6, Issue: 2 259-278 International Journal of Assessment Tools in Education |
| ISSN: | 2148-7456 |
| Popis: | 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 (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. Item response theory is a widely used framework for thedesign, scoring, and scaling of measurement instruments. Item response modelsare typically used for dichotomously scored questions that have only two scorepoints (e.g., multiple-choice items). However, given the increasing use ofinstruments that include questions with multiple response categories, such assurveys, questionnaires, and psychological scales, polytomous item responsemodels are becoming more utilized in education and psychology. This study aimsto demonstrate the application of explanatory item response models to polytomousitem responses in order to explain common variability in item clusters, persongroups, and interactions between item clusters and person groups. Explanatoryforms of several polytomous item response models – such as Partial Credit Modeland Rating Scale Model – are demonstrated and the estimation procedures ofthese models are explained. Findings of this study suggest that explanatoryitem response models can be more robust and parsimonious than traditional itemresponse models for polytomous data where items and persons share common characteristics.Explanatory polytomous item response models can provide more information aboutresponse patterns in item responses by estimating fewer item parameters. |
| Databáze: | OpenAIRE |
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