Brandon LeBeau
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Differentiating Among Gifted Learners: A Comparison of Classical Test Theory and Item Response Theory on Above-Level Testing

IRT
Gifted Education
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 abo…
Authors

Brandon LeBeau

Susan G. Assouline

Duhita Mahatmya

Ann Lupkowski-Shoplik

Published

June 1, 2020

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 case study to compare estimates from classical test theory (CTT) and IRT. First, we estimated means, standard deviations, and percentiles of the students using CTT statistics. Next, we fitted a two- parameter IRT model using a multi-group framework to represent the different grade levels. We compared CTT and IRT results to determine the value-added of using an IRT approach in identifying high-achieving students through the Talent Search Model of above-level testing. Benefits of IRT, compared to CTT and with respect to the Talent Search Model, include invariance of item parameters across groups of individuals and invariance of an individual’s ability across tests of the same construct. IRT also uses the response string of individuals’ scores; therefore, test items can differentially inform the latent aptitude construct. Implications for academic talent identification with the Talent Search Model and development of academic talent are discussed.

Citation

LeBeau, Brandon, Assouline, Susan G., Mahatmya, Duhita, Lupkowski-Shoplik, Ann (2020). Differentiating Among Gifted Learners: A Comparison of Classical Test Theory and Item Response Theory on Above-Level Testing. **Gifted Child Quarterly, 64 (3), 219-237.

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Publication: Gifted Child Quarterly, 64 (3), 219-237 Authors: Brandon LeBeau, Susan G. Assouline, Duhita Mahatmya, Ann Lupkowski-Shoplik Date: June 01, 2020 DOI: 10.1177/0016986220924050

 

Brandon LeBeau