Expanding Gifted Identification to Capture Academically Advanced, Low-Income, or Other Disadvantaged Students: The Case of Arkansas.

Tran, Bich Thi Ngoc; Wai, Jonathan; McKenzie, Sarah; Mills, Jonathan; Seaton, Dustin

We examined the state of Arkansas, empirically testing how focusing on high-achieving students using state tests might expand the pool of gifted identified students. From a broader sample of 173,133 students, we compared the degree to which students who were academically talented in the top 5% on third-grade state literacy and math assessments were identified as gifted in Arkansas. Across five independent cohorts, we replicated the finding that roughly 30% of the students in the top 5% on both third-grade literacy and math were not identified as gifted. Logistic regression (N = 3992) indicated that high-achieving students participating in the federal Free/Reduced Lunch program were 50% less likely to be identified. These findings suggest that using state math and literacy assessments as universal screening tools could improve gifted identification of high-achieving students, many from low-income or other disadvantaged backgrounds.

ARKANSAS; GIFTED & talented education; GIFTED persons; LOGISTIC regression analysis; STUDENTS

Journal for the Education of the Gifted, 2022, Vol 45, Issue 1, p64

0162-3532

Academic Journal

10.1177/01623532211063936