A Meta-Analysis of Gifted and Talented Identification Practices

Autor/inn/en	Hodges, Jaret; Tay, Juliana; Maeda, Yukiko; Gentry, Marcia
Titel	A Meta-Analysis of Gifted and Talented Identification Practices
Quelle	In: Gifted Child Quarterly, 62 (2018) 2, S.147-174 (28 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Gentry, Marcia)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1934-9041
DOI	10.1177/0016986217752107
Schlagwörter	Meta Analysis; Academically Gifted; Talent Identification; Disproportionate Representation; Minority Group Students; African American Students; Hispanic American Students; American Indian Students; Nonverbal Tests; Portfolio Assessment; Check Lists; Effect Size; Asian American Students; White Students; Comparative Analysis; Equal Education; Risk; Coding; Elementary School Students; Secondary School Students; Statistical Analysis; Literature Reviews + Suchen Sie Ihr Suchwort? Meta-analysis; Metaanalyse; Begabtenanalyse; Talentsuche; African Americans; Student; Students; Afroamerikaner; Schüler; Schülerin; Studentin; Hispanic; Hispanic Americans; Hispanoamerikaner; Portfoliobeurteilung; Checkliste; Asian immigrant; United States; Asiatischer Einwanderer; USA; Risiko; Codierung; Programmierung; Sekundarschüler; Statistische Analyse
Abstract	Researchers consider the underrepresentation of Black, Hispanic, and Native American students is largely due to the use of traditional methods of identification (i.e., IQ and standardized achievement tests). To address this concern, researchers created novel nontraditional identification methods (e.g., nonverbal tests, student portfolios, affective checklists). This meta-analysis of 54 studies, consisting of 85 effect sizes representing 191,287,563 students, provides evidence that nontraditional identification methods, while able to narrow the proportional identification gap between underrepresented (Black, Hispanic, and Native American) and represented (Asian and White American) populations, are still unable to address the issue of education inequity. An overall risk ratio of 0.34 was calculated for nontraditional methods of identification in comparison with a 0.27 risk ratio for traditional methods. While the nontraditional methods help identify more underrepresented students as gifted, the results of this meta-analysis show that better identification methods are needed to address inequities in identification. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01