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The C-Test is a variation of the cloze test with the same basic theoretical assumptions. The C-Test is based on the reduced redundancy principle. The current study is an attempt to examine the effect of 13 factors on item difficulty in C-Test items based on construct identification approach to validation. For analyzing the data, correlational analysis, multiple regression, one-way analysis of variance, and the linear logistic test model were used. The results showed that the frequency of mutilated words, content words, and text difficulty as measured by gap p-values have a significant…mehr

Produktbeschreibung
The C-Test is a variation of the cloze test with the same basic theoretical assumptions. The C-Test is based on the reduced redundancy principle. The current study is an attempt to examine the effect of 13 factors on item difficulty in C-Test items based on construct identification approach to validation. For analyzing the data, correlational analysis, multiple regression, one-way analysis of variance, and the linear logistic test model were used. The results showed that the frequency of mutilated words, content words, and text difficulty as measured by gap p-values have a significant correlation with item difficulty. So, it was revealed that there are significance differences among the mean difficulties of different word classes. Verbs and adjectives were harder to reconstruct for participants and determiners were easier. The results of multiple regression revealed that the word and text characteristics explain 8% of variance in item difficulties. The linear logistic test modeling also confirmed the regression results. The result of this analysis showed that content words, inflections, and the frequency of the mutilated words had the greatest impact on item difficulty.
Autorenporträt
Fahime Khoshdel Niyat is English instructor and translator. She obtained a masters¿ degree in teaching English as a foreign language from Islamic Azad University, Mashhad Branch, Mashhad, Iran. Her research interests are in language testing and assessment and data analysis.