Adding Design Elements to Improve Time Series Designs: No Child Left behind as an Example of Causal Pattern-Matching

Autor/inn/en	Wong, Manyee; Cook, Thomas D.; Steiner, Peter M.
Titel	Adding Design Elements to Improve Time Series Designs: No Child Left behind as an Example of Causal Pattern-Matching
Quelle	In: Journal of Research on Educational Effectiveness, 8 (2015) 2, S.245-279 (35 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	Weitere Informationen
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1934-5747
DOI	10.1080/19345747.2013.878011
Schlagwörter	Evaluation Methods; Time; Federal Legislation; Educational Legislation; Research Design; Inferences; Research Methodology; Comparative Analysis; Public Schools; Catholic Schools; State Standards; National Standards; Academic Achievement; Causal Models; Institutional Characteristics; Regression (Statistics); Grade 4; Grade 8; Mathematics Achievement; Reading Achievement; Scores; Effect Size; Prediction; Theories; Racial Differences; Hispanic American Students; African American Students; White Students; Racial Composition; National Assessment of Educational Progress + Suchen Sie Ihr Suchwort? Zeit; Bundesrecht; Bildungsrecht; Schulgesetz; Forschungsdesign; Inference; Inferenz; Research method; Forschungsmethode; Public school; Öffentliche Schule; Katholische Schule; Schulleistung; Kausalanalyse; Regression; Regressionsanalyse; School year 04; 4. Schuljahr; Schuljahr 04; School year 08; 8. Schuljahr; Schuljahr 08; Mathmatics sikills; Mathmatics achievement; Mathematical ability; Mathematische Kompetenz; Leseleistung; Vorhersage; Theory; Theorie; Rassenunterschied; Hispanic; Hispanic Americans; Student; Students; Hispanoamerikaner; Schüler; Schülerin; Studentin; African Americans; Afroamerikaner
Abstract	Some form of a short interrupted time series (ITS) is often used to evaluate state and national programs. An ITS design with a single treatment group assumes that the pretest functional form can be validly estimated and extrapolated into the postintervention period where it provides a valid counterfactual. This assumption is problematic. Ambiguous preintervention functional forms are common, as are other factors affecting posttest means and slopes. Using No Child Left Behind as an example, we demonstrate how adding multiple design elements to the basic ITS structure serves to promote causal inference by limiting alternative interpretations. No added design element is perfect by itself, but we argue that they "collectively" provide a strong causal warrant when the predictions they engender are complex, the results "cohere" with the predictions, and no alternative can fit the same pattern of predictions even if it can fit some of them. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2022/4/11