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Peters, Scott J.; Rambo-Hernandez, Karen; Makel, Matthew C.; Matthews, Michael S.; Plucker, Jonathan A. – AERA Open, 2019
Educators have sought to understand and address the disproportional representation of students from certain student subgroups in gifted education. Most gifted identification decisions are made with national comparisons where students must score above a certain percentage of test takers. However, this approach is not always consistent with the…
Descriptors: Academically Gifted, Student Diversity, Racial Differences, Ethnicity
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Tran, Bich Thi Ngoc; Wai, Jonathan; McKenzie, Sarah; Mills, Jonathan; Seaton, Dustin – Journal for the Education of the Gifted, 2022
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…
Descriptors: Academically Gifted, Talent Identification, High Achievement, Low Income Students
Daniel A. Long; D. Betsy McCoach; Del Siegle; Carolyn M. Callahan; E. Jean Gubbins – Grantee Submission, 2023
Is under-representation of Black, Latinx, English learners (EL), and students from economically challenging communities in gifted programs due to inequality in early academic achievement or bias in the gifted identification process? Using three-level multilevel logistic models, we examine the degree to which the disparities in gifted…
Descriptors: Academically Gifted, Gifted Education, Disproportionate Representation, Minority Group Students
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Sorensen, Lucy C. – Educational Administration Quarterly, 2019
Purpose: In an era of unprecedented student measurement and emphasis on data-driven educational decision making, the full potential for using data to target resources to students has yet to be realized. This study explores the utility of machine-learning techniques with large-scale administrative data to identify student dropout risk. Research…
Descriptors: At Risk Students, Dropouts, Data Collection, Data Analysis
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Garrett, Rachel; Davis, Elisabeth; Eisner, Ryan – Regional Educational Laboratory Midwest, 2019
Cleveland Metropolitan School District (CMSD) has witnessed an increase in the number of English learner students in grades K-12 over recent years, with students coming from more diverse backgrounds in race/ethnicity, countries of origin, and native language. This requires more support from the district to meet diverse needs in terms of languages,…
Descriptors: Elementary Secondary Education, Grade 3, Grade 4, Grade 5
Kim, JoHyun; Watkins, Sandra; Yoon, Seung Won – Education Leadership Review, 2016
This study examined the achievement trends of advanced learners and the relationship between Illinois' school district characteristics and student performance using Illinois Standards Achievement Test (ISAT) scores. The 3rd grade students scoring in the Exceeds category in ISAT reading and math within 707 Illinois school districts during the…
Descriptors: Trend Analysis, Academic Achievement, Academically Gifted, Scores
Holmes, Venita R. – Houston Independent School District, 2018
This study hypothesized that HISD prekindergarten participation consistently correlated with better educational outcomes for students. Taking into account students' age differences through kindergarten enrollment, propensity score matching controlled for students' background characteristics. Three cohorts of students in this study were eligible or…
Descriptors: Language Proficiency, Mathematics Achievement, Reading Achievement, Language Arts
Sarouphim, Ketty M.; Maker, C. June – Online Submission, 2009
The purpose of this study was to examine ethnic and gender differences in using DISCOVER, a performance-based assessment, for identifying gifted students from diverse ethnicities. DISCOVER is an acronym which stands for Discovering Intellectual Strength and Capabilities while Observing Varied Ethnic Responses. The sample consisted of 941 boys and…
Descriptors: Ethnicity, Differences, Gender Differences, Performance Based Assessment