Multidimensional IRT Analysis of Reading Comprehension in English as a Foreign Language
- Title
- Multidimensional IRT Analysis of Reading Comprehension in English as a Foreign Language
- Abstract
-
Unidimensionality is an important assumption of measurement but it is violated very often. Most of the time, tests are deliberately constructed to be multidimensional to cover all aspects of the intended construct. In such situations, the application of unidimensional item response theory (IRT) models is not justified due to poor model fit and misleading results. Multidimensional IRT (MIRT) models can handle several dimensions simultaneously and yield person ability parameters on several dimensions which is helpful for diagnostic purposes too. Furthermore, MIRT models use the correlation between the dimensions to enhance the precision of the measurement. In this study a reading comprehension test is modelled with the multidimensional Rasch model. The findings showed that a correlated 2-dimensional model has the best fit to the data. The bifactor model revealed some interesting information about the structure of reading comprehension and the reading curriculum. Implications of the study for the testing and teaching of reading comprehension are discussed.
- Scientific Type
- غير معروف
- Journal volume
- vol.13,sepcial
- Collaboration type
- مشترك
- Publish Date
- March 1, 2023
- Participated Universities (Publication)
-
Alnoor University
- Scopus status
- In Scopus
- Scopus index year
- 2 023
- Scopus quarter
- 1
- Scopus citation score
- 2.099999905
- Clarivate status
- Not In Clarivate
- Pub. Med. status
- Not In PubMed
- Author (Publication)
-
إسماعيل عبد الوهاب إسماعيل محمد
- Journal (Publication)
-
International Journal of Language Testing
- Publisher (Publication)
- Tabaran Institute of Higher Education (Iran Ministry of Sciences)
- ISSN
- 2476-5880
- Country (Publication)
-
Iran
- Country type
- عالمية
- College (Publication)
-
College of Education
- Departement (Publication)
-
Department of English Language
- Media
-
Academic Paper
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