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ERIC Number: EJ1206211
Record Type: Journal
Publication Date: 2019-Jan
Pages: 6
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-1307-9298
EISSN: N/A
Available Date: N/A
Use of Mixed Item Response Theory in Rating Scales
Yalçin, Seher
International Electronic Journal of Elementary Education, v11 n3 p273-278 Jan 2019
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.
International Electronic Journal of Elementary Education. T&K Akademic Rosendalsvein 45, Oslo 1166, Norway. e-mail: iejee@iejee.com; Web site: https://www.iejee.com/index.php/IEJEE/index
Publication Type: Journal Articles; Reports - Research
Education Level: Middle Schools; Secondary Education; Junior High Schools; Grade 8; Elementary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Location: Turkey
Grant or Contract Numbers: N/A
Author Affiliations: N/A