B. Tran, Jonathan Wai, S. McKenzie, Jonathan N. Mills, Dustin Seaton
{"title":"Expanding Gifted Identification to Capture Academically Advanced, Low-Income, or Other Disadvantaged Students: The Case of Arkansas","authors":"B. Tran, Jonathan Wai, S. McKenzie, Jonathan N. Mills, Dustin Seaton","doi":"10.1177/01623532211063936","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":51648,"journal":{"name":"JOURNAL FOR THE EDUCATION OF THE GIFTED","volume":"45 1","pages":"64 - 83"},"PeriodicalIF":1.2000,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"JOURNAL FOR THE EDUCATION OF THE GIFTED","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/01623532211063936","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"EDUCATION, SPECIAL","Score":null,"Total":0}
引用次数: 1
Abstract
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.