Preprint
Differentiating Among High-Achieving Learners: A Comparison of Classical Test Theory and Item Response Theory on Above-Level Testing
Iowa Research Online
University of Iowa
12/04/2019
DOI: 10.17077/pp.004118
Abstract
This study investigated the application of item response theory (IRT) to expand the range of ability estimates for gifted (hereinafter referred to as high-achieving) students’ performance on an above-level test. Using a sample of 4th – 6th grade high-achieving students (n = 1,893), we conducted a study to compare estimates from two measurement theories, classical test theory (CTT) and IRT. CTT and IRT make different assumptions about the analysis that impact the reliability and validity of the scores obtained from the test. IRT can also differentiate students based on the student’s grade or within a grade by using the unique string of correct and incorrect answers the student makes while taking the test. This differentiation may have implications for identifying or classifying students who are ready for advanced coursework. An exploration of the differentiation for math, reading, and science tests and the impact the different measurement frameworks can have on classification of students are explored. Implications for academic talent identification with the Talent Search Model and development of academic talent are discussed.
Details
- Title: Subtitle
- Differentiating Among High-Achieving Learners: A Comparison of Classical Test Theory and Item Response Theory on Above-Level Testing
- Creators
- Brandon C LeBeau - University of Iowa, Psychological and Quantitative FoundationsSusan G Assouline - University of Iowa, Psychological and Quantitative FoundationsDuhita Mahatmya - University of Iowa, Education AdministrationAnn Lupkowski-Shoplik - University of Iowa, Belin-Blank Center
- Resource Type
- Preprint
- Publication Details
- Iowa Research Online
- DOI
- 10.17077/pp.004118
- eISSN
- 2476-1680
- Publisher
- University of Iowa; Iowa City, Iowa, USA
- Number of pages
- 42 pages
- Copyright
- Copyright © 2019 the authors
- Language
- English
- Date posted
- 12/04/2019
- Academic Unit
- Iowa Neuroscience Institute; Center for Social Science Innovation; Psychological and Quantitative Foundations
- Record Identifier
- 9983740197502771
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