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Baghaei, Samira; Bagheri, Mohammad Sadegh; Yamini, Mortaza – Cogent Education, 2020
The main purpose of this quantitative-qualitative content analysis study was to compare IELTS and TOEFL listening and reading tests based on the representation of the learning objectives of Revised Bloom's taxonomy. To this end, 12 Academic IELTS listening and reading tests and 12 TOEFL iBT listening and reading tests were analyzed qualitatively…
Descriptors: Second Language Learning, English (Second Language), Language Tests, Reading Tests
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Cawthon, Stephanie – American Annals of the Deaf, 2011
Linguistic complexity of test items is one test format element that has been studied in the context of struggling readers and their participation in paper-and-pencil tests. The present article presents findings from an exploratory study on the potential relationship between linguistic complexity and test performance for deaf readers. A total of 64…
Descriptors: Language Styles, Test Content, Syntax, Linguistics
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Sawaki, Yasuyo; Kim, Hae-Jin; Gentile, Claudia – Language Assessment Quarterly, 2009
In cognitive diagnosis a Q-matrix (Tatsuoka, 1983, 1990), which is an incidence matrix that defines the relationships between test items and constructs of interest, has great impact on the nature of performance feedback that can be provided to score users. The purpose of the present study was to identify meaningful skill coding categories that…
Descriptors: Feedback (Response), Test Items, Test Content, Identification
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Schroeder, Carolyn M.; Scott, Timothy P.; Tolson, Homer; Huang, Tse-Yang; Lee, Yi-Hsuan – Journal of Research in Science Teaching, 2007
This project consisted of a meta-analysis of U.S. research published from 1980 to 2004 on the effect of specific science teaching strategies on student achievement. The six phases of the project included study acquisition, study coding, determination of intercoder objectivity, establishing criteria for inclusion of studies, computation of effect…
Descriptors: Test Format, Test Content, Academic Achievement, Meta Analysis