Heterogeneity in Mathematics Intervention Effects: Evidence from a Meta-Analysis of 191 Randomized Experiments

Autor/inn/en	Williams, Ryan; Citkowicz, Martyna; Miller, David I.; Lindsay, Jim; Walters, Kirk
Titel	Heterogeneity in Mathematics Intervention Effects: Evidence from a Meta-Analysis of 191 Randomized Experiments
Quelle	In: Journal of Research on Educational Effectiveness, 15 (2022) 3, S.584-634 (51 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	Weitere Informationen
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1934-5747
DOI	10.1080/19345747.2021.2009072
Schlagwörter	Meta Analysis; Mathematics Education; Educational Change; Difficulty Level; Academic Standards; Intervention; Preschool Education; Elementary Secondary Education; Research Reports; Effect Size; Mathematics Achievement; Research Methodology; Teaching Methods; Predictor Variables; Technology Uses in Education; Instructional Program Divisions; Comparative Analysis + Suchen Sie Ihr Suchwort? Meta-analysis; Metaanalyse; Mathematische Bildung; Bildungsreform; Schwierigkeitsgrad; Pre-school education; Vorschulerziehung; Research report; Forschungsbericht; Mathmatics sikills; Mathmatics achievement; Mathematical ability; Mathematische Kompetenz; Research method; Forschungsmethode; Teaching method; Lehrmethode; Unterrichtsmethode; Prädiktor; Technology enhanced learning; Technology aided learning; Technologieunterstütztes Lernen
Abstract	Since the standards-based education movement began in the early 1990s, mathematics education reformers have developed and evaluated many interventions to support students in mastering more rigorous content. We conducted a systematic review and meta-analysis of U.S. PreK-12 mathematics intervention effects from 1991 to 2017 to study sources of heterogeneity. From more than 9,000 published and unpublished study reports, we found 191 randomized control trials that met our inclusion criteria, with 1,109 effect size estimates representing more than a quarter of a million students. The average effect size on student mathematics achievement was 0.31, with wide heterogeneity of most effects ranging from -0.60 to 1.23. Two modeling approaches--meta-regression and machine learning--provided converging evidence that outcome measure type (researcher-created vs. standardized) and technology delivery (vs. teacher or interventionist delivery) were predictors of effect size. Intervention type, intervention length, grade level, and publication year were also identified as potentially explanatory factors. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01