Translating Standardized Effects of Education Programs into More Interpretable Metrics

Autor/inn/en	Baird, Matthew D.; Pane, John F.
Titel	Translating Standardized Effects of Education Programs into More Interpretable Metrics
Quelle	In: Educational Researcher, 48 (2019) 4, S.217-228 (12 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Baird, Matthew D.) ORCID (Pane, John F.)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0013-189X
DOI	10.3102/0013189X19848729
Schlagwörter	Outcomes of Education; Program Evaluation; Educational Policy; Evaluators; Data Interpretation; Outcome Measures; Achievement Gap; Benchmarking; Individualized Instruction; Progress Monitoring; Reading Achievement; Mathematics Achievement; Time Factors (Learning); Growth Models; African American Students; White Students; Rural Urban Differences; Low Income; Disadvantaged Environment; Elementary School Students; Secondary School Students; Research Utilization; Achievement Tests; Measures of Academic Progress + Suchen Sie Ihr Suchwort? Lernleistung; Schulerfolg; Programme evaluation; Programmevaluation; Politics of education; Bildungspolitik; Data evaluation; Datenauswertung; Individualisierender Unterricht; Leseleistung; Mathmatics sikills; Mathmatics achievement; Mathematical ability; Mathematische Kompetenz; African Americans; Student; Students; Afroamerikaner; Schüler; Schülerin; Studentin; Stadt-Land-Beziehung; Niedriglohn; Sekundarschüler; Forschungsumsetzung; Achievement test; Achievement; Testing; Test; Tests; Leistungsbeurteilung; Leistungsüberprüfung; Leistung; Testdurchführung; Testen
Abstract	Evaluators report effects of education initiatives as standardized effect sizes, a scale that has merits but obscures interpretation of the effects' practical importance. Consequently, educators and policymakers seek more readily interpretable translations of evaluation results. One popular metric is the number of years of learning necessary to induce the effect. We compare years of learning to three other translation options: benchmarking against other effect sizes, converting to percentile growth, and estimating the probability of scoring above a proficiency threshold. After enumerating the desirable properties of translations, we examine each option's strengths and weaknesses. We conclude that years of learning performs worst, and percentile gains performs best, making it our recommended choice for more interpretable translations of standardized effects. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01