Psychology, Evaluation, and Technology in Educational Research
Vol. 5 No. 1 (2022)

Polytomous scoring correction and its effect on the model fit: A case of item response theory analysis utilizing R

Agus Santoso (Universitas Terbuka)
Timbul Pardede (Universitas Terbuka)
Ezi Apino (Universitas Negeri Yogyakarta)
Hasan Djidu (Universitas Sembilanbelas November Kolaka)
Ibnu Rafi (Universitas Negeri Yogyakarta)
Munaya Nikma Rosyada (Universitas Negeri Yogyakarta)
Heri Retnawati (Universitas Negeri Yogyakarta)
Gulzhaina K. Kassymova (Satbayev University
Abai Kazakh National Pedagogical University)



Article Info

Publish Date
13 Dec 2022

Abstract

In item response theory, the number of response categories used in polytomous scoring has an effect on the fit of the model used. When the initial scoring model yields unsatisfactory estimates, corrections to the initial scoring model need to be made. This exploratory descriptive study used response data from Take Home Exam (THE) participants in the Statistical Methods I course organized by the Open University, Indonesia, in 2022. The stages of data analysis include coding the rater’s score; analyzing frequency; analyze the fit of the model based on graded, partial, and generalized partial credit models; analyze the characteristic response function (CRF) curve; scoring correction (rescaling); and re-analyze the fit of the model. The fit of the model is based on the chi-square test and the root mean square error of approximation (RMSEA). All model fit analyzes were performed by using R. The results revealed that scoring corrections had an effect on model fit and that the partial credit model (PCM) produced the best item parameter estimates. All results and their implications for practice and future research are discussed.

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Journal Info

Abbrev

PETIER

Publisher

Subject

Computer Science & IT Education Social Sciences

Description

Psychology, Evaluation, and Technology in Educational Research is a peer reviewed open-access journal which publishes educational research articles in psychology, evaluation, and technology. Every submitted manuscript will be reviewed by at least two peer-reviewers using double blind review ...