Propensity Score Matching Helps to Understand Sources of DIF and Mathematics Performance Differences of Indonesian, Turkish, Australian, and Dutch Students in PISA

Autor/inn/en	Arikan, Serkan; van de Vijver, Fons J. R.; Yagmur, Kutlay
Titel	Propensity Score Matching Helps to Understand Sources of DIF and Mathematics Performance Differences of Indonesian, Turkish, Australian, and Dutch Students in PISA
Quelle	In: International Journal of Research in Education and Science, 4 (2018) 1, S.69-81 (14 Seiten) PDF als Volltext kostenfreie Datei Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	2148-9955
Schlagwörter	Probability; Test Bias; Mathematics Instruction; Foreign Countries; Achievement Tests; International Assessment; Secondary School Students; Structural Equation Models; Regression (Statistics); Predictor Variables; Mathematics Achievement; Mathematics Tests; Cross Cultural Studies; Indonesia; Turkey; Australia; Netherlands; Program for International Student Assessment + Suchen Sie Ihr Suchwort? Wahrscheinlichkeitsrechnung; Wahrscheinlichkeitstheorie; Testkritik; Mathematics lessons; Mathematikunterricht; Ausland; Achievement test; Achievement; Testing; Test; Tests; Leistungsbeurteilung; Leistungsüberprüfung; Leistung; Testdurchführung; Testen; Sekundarschüler; Regression; Regressionsanalyse; Prädiktor; Mathmatics sikills; Mathmatics achievement; Mathematical ability; Mathematische Kompetenz; Cultural comparison; Kulturvergleich; Indonesien; Türkei; Australien; Niederlande
Abstract	We examined Differential Item Functioning (DIF) and the size of cross-cultural performance differences in the Programme for International Student Assessment (PISA) 2012 mathematics data before and after application of propensity score matching. The mathematics performance of Indonesian, Turkish, Australian, and Dutch students on released items was compared. Matching variables were gender, an index of economic, social and cultural status, and opportunity to learn, in exact, nearest neighbor, and optimal matching. Logistic regression and structural equation modeling were used to identify DIF. If propensity scores were used in the DIF analyses as performance predictors, much less DIF was found than in the original data; similarly, when in tests of country differences in mathematics performance, propensity scores were used as covariates, effect sizes of tests of country differences were reduced substantially. We concluded that propensity scoring provided us with a new tool to better control sources of DIF and country differences in PISA mathematics performance. (As Provided).
Anmerkungen	International Journal of Research in Education and Science. Necmettin Erbakan University, Ahmet Kelesoglu Education Faculty, Meram, Konya 42090 Turkey. e-mail: ijresoffice@gmail.com; Web site: http://www.ijres.net
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01