Use of Mixed Item Response Theory in Rating Scales

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Seher Yalçın

Abstract

This study aimed to compare the Graded Response Model (GRM) and the Mixed-Graded Response Model (MixGRM) in terms of model data-fit and parameters and demonstrate the application of MixGRM on real data. In this context, this study is basic research based on the International Computer and Information Literacy Study in 2013 conducted with eighth-grade participants from Turkey. The data from a total of 2,356 students were used in the study. In testing the models, data was obtained from an 11-item Likert scale that measured the students' interest and enjoyment in using Information and Communication Technologies (ICTs). When the GRM- and MixGRM-based model data-fit results were compared, the model with the best fit was the MixGRM with four latent classes. Students who reported to enjoy using ICT and who had the highest computer and information literacy (CIL) score were found to be in the first latent class, those with least enjoyment or dislike and those with the lowest CIL score were in the fourth latency class. The findings show that reducing the heterogeneity of Mixed-Item Response Theory models in the dataset is a preferable model for research situations and that Turkish students are not yet prepared for life in the digital age.

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YALÇIN, Seher. Use of Mixed Item Response Theory in Rating Scales. International Electronic Journal of Elementary Education, [S.l.], v. 11, n. 3, p. 273-278, feb. 2019. ISSN 1307-9298. Available at: <https://iejee.com/index.php/IEJEE/article/view/675>. Date accessed: 20 mar. 2019.
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