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

IF 1.2 Q3 EDUCATION, SPECIAL
B. Tran, Jonathan Wai, S. McKenzie, Jonathan N. Mills, Dustin Seaton
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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.
扩大天才鉴定,以捕获学习成绩优秀、低收入或其他弱势学生:阿肯色州的案例
我们调查了阿肯色州,实证测试了使用州测试关注成绩优异的学生如何扩大天才学生的群体。从173133名学生的更广泛样本中,我们比较了在阿肯色州,在三年级州识字和数学评估中,学业天赋排名前5%的学生被认定为天才的程度。在五个独立的队列中,我们重复了这一发现,即在三年级识字和数学成绩排名前5%的学生中,大约有30%的人没有被认定为天才。Logistic回归(N=3992)表明,参加联邦免费/减少午餐计划的成绩优异的学生被识别的可能性降低了50%。这些发现表明,使用州数学和识字率评估作为通用筛选工具,可以提高对成绩优异学生的天赋识别,其中许多学生来自低收入或其他弱势背景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
3.00
自引率
0.00%
发文量
17
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