On Estimating Achievement Dynamic Models from Repeated Cross Sections

Autor/inn/en	Contini, Dalit; Grand, Elisa
Titel	On Estimating Achievement Dynamic Models from Repeated Cross Sections
Quelle	In: Sociological Methods & Research, 46 (2017) 4, S.988-1017 (30 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0049-1241
DOI	10.1177/0049124115613773
Schlagwörter	Academic Achievement; Case Studies; Longitudinal Studies; Achievement Gap; Regression (Statistics); Grade 5; Grade 6; Elementary School Students; Foreign Countries; Models; Surveys; Individual Characteristics; Standardized Tests; Comparative Analysis; Statistical Analysis; Italy + Suchen Sie Ihr Suchwort? Schulleistung; Case study; Fallstudie; Case Study; Longitudinal study; Longitudinal method; Longitudinal methods; Längsschnittuntersuchung; Regression; Regressionsanalyse; School year 05; 5. Schuljahr; Schuljahr 05; School year 06; 6. Schuljahr; Schuljahr 06; Ausland; Analogiemodell; Survey; Umfrage; Befragung; Personality characteristic; Personality traits; Persönlichkeitsmerkmal; Standadised tests; Standardisierter Test; Statistische Analyse; Italien
Abstract	Despite the increasing spread of standardized assessments of student learning, longitudinal data on achievement data are still lacking in many countries. This article raises the following question: Can we exploit cross-sectional assessments held at different schooling stages to evaluate how achievement inequalities related to individual-ascribed characteristics develop over time? This is a highly policy relevant issue, as achievement inequalities may develop in substantially different ways across educational systems. We discuss the issues involved in estimating dynamic models from repeated cross-sectional surveys in this context; consistently with a simple learning accumulation model, we propose an imputed regression strategy that allows to "link" two surveys and deliver consistent estimates of the parameters of interest. We then apply the method to Italian achievement data of fifth and sixth graders and investigate how inequalities develop between primary and lower secondary school. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01