Differential Prediction Generalization in College Admissions Testing

Autor/inn/en	Aguinis, Herman; Culpepper, Steven A.; Pierce, Charles A.
Titel	Differential Prediction Generalization in College Admissions Testing
Quelle	In: Journal of Educational Psychology, 108 (2016) 7, S.1045-1059 (15 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0022-0663
DOI	10.1037/edu0000104
Schlagwörter	Quantitative Daten; Prediction; Grade Point Average; High School Students; College Freshmen; Scores; Ethnic Groups; Gender Differences; College Entrance Examinations; African American Students; White Students; Hispanic American Students; Generalization; Test Bias; Statistical Analysis; Racial Differences; SAT (College Admission Test) + Suchen Sie Ihr Suchwort? Vorhersage; High school; High schools; Student; Students; Oberschule; Schüler; Schülerin; Studentin; Studienanfänger; Ethnie; Geschlechterkonflikt; Aufnahmeprüfung; African Americans; Afroamerikaner; Hispanic; Hispanic Americans; Hispanoamerikaner; Testkritik; Statistische Analyse; Rassenunterschied
Abstract	We introduce the concept of "differential prediction generalization" in the context of college admissions testing. Specifically, we assess the extent to which predicted first-year college grade point average (GPA) based on high-school grade point average (HSGPA) and SAT scores depends on a student's ethnicity and gender and whether this difference varies across samples. We compared 257,336 female and 220,433 male students across 339 samples, 29,734 Black and 304,372 White students across 247 samples, and 35,681 Hispanic and 308,818 White students across 264 samples collected from 176 colleges and universities between the years 2006 and 2008. Overall, results show a lack of differential prediction generalization because variability remains after accounting for methodological and statistical artifacts including sample size, range restriction, proportion of students across ethnicity- and gender-based subgroups, subgroup mean differences on the predictors (i.e., HSGPA, SAT-Critical Reading, SAT-Math, and SAT-Writing), and SDs for the predictors. We offer an agenda for future research aimed at understanding several contextual reasons for a lack of differential prediction generalization based on ethnicity and gender. Results from such research will likely lead to a better understanding of the reasons for differential prediction and interventions aimed at reducing or eliminating it when it exists. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01