Use of Mixed Item Response Theory in Rating Scales

Seher Yalçın

Vol. 11 No. 3 (2019) Special Issue: The Use of ICT in Education

Use of Mixed Item Response Theory in Rating Scales

Seher Yalçın

Published February 7, 2019 | Pages: 273-278 | Views: 334

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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.

<p>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.</p>

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References

Gardner, D. G., Dukes, R. L., & Discenza, R. (1993). Effects of computer use on computer attitudes and computer confidence: A causal modeling approach. Computers in Human Behavior, 9, 427-440.

Gerick, J., Eickelmann, B., & Bos, W. (2017). The international computer and information literacy study from a European perspective: Introduction to the Special Issue. European Educational Research Journal, 16(6), 707–715.

Güzeller, C. O. (2011). PISA 2009 Türkiye örnekleminde öğrencilerin bilgisayar öz-yeterlik inançları ve bilgisayar tutumları arasındaki ilişkinin incelenmesi. Kırşehir Eğitim Fakültesi Dergisi, 12, 183-203.

Hambleton, R. K. & Swaminathan, H. (1985). Item response theory: Principles and application. Boston: Kluwer Academic Publishers Group.

Hambleton, R. K., Swaminathan, H. & Rogers, H. J. (1991). Fundamentals of item response theory. California: Sage Publications Inc.

Huang, H. Y. (2016). Mixture random-effect IRT models for controlling extreme response style on rating scales. Frontiers in Psychology, 7(1706), 1-15. doi: 10.3389/fpsyg.2016.01706.

Maij-de Meij, A. M., Kelderman, H., & Van der Flier, H. (2008). Fitting a mixture item response theory model to personality questionnaire data: Characterizing latent classes and investigating possibilities for improving prediction. Applied Psychological Measurement, 32, 611–631.

Ölmez, İ. B. & Cohen, A. S. (2018). A mixture partial credit analysis of math anxiety. International Journal of Assessment Tools in Education, 5(4), 611–630. DOI: 10.21449/ijate.455175.

Partnership for 21st Century Learning (P21). (2007). Framework for 21st century learning. http://www.p21.org/our-work/p21-framework adresinden alındı.

Rohatgi, A., Scherer, R. & Hatlevik, O. E. (2016). The role of ICT self-efficacy for students' ICT use and their achievement in a computer and information literacy test. Computers & Education, 102, 103-116. Doi: 10.1016/j.compedu.2016.08.001.

Scherer, R., Rohatgi, A. & Hatlevik, O. E. (2017). Students' profiles of ICT use: Identification, determinants, and relations to achievement in a computer and information literacy test. Computers in Human Behavior, 70, 486-499.

The International Association for the Evaluation of Educational Achievement (IEA). (2014). Press release. https://www.iea.nl/sites/default/files/studies/IEA%20ICILS%202013%20Press%20Release.pdf

Trilling, B. & Fadel, C. (2009). 21st-century skills: Learning for life in our times. Francisco: Jossey-Bass.

von Davier, M. & Rost, J. (2017). Logistic mixture-distribution response models. In W. J. van der Linden (Ed.), Handbook of item response theory, volume one: Models (p. 393-406). Boca Raton: Chapman and Hall/CRC.

Yalçın, S. (2018). Data fit comparison of mixture item response theory models and traditional models. International Journal of Assessment Tools in Education, 5(2), 301-313. doi: 10.21449/ijate.402806.

Keywords

graded response model, mixture item response theory, latent class analysis, mixture graded response model, information and communication technologies

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Seher Yalçın

Ankara University

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How to Cite

Yalçın, S. (2019). Use of Mixed Item Response Theory in Rating Scales. International Electronic Journal of Elementary Education, 11(3), 273–278. Retrieved from https://iejee.com/index.php/IEJEE/article/view/675