A Multilevel Latent Growth Curve Approach to Predicting Student Proficiency

Autor/inn/en	Choi, Kilchan; Goldschmidt, Pete
Titel	A Multilevel Latent Growth Curve Approach to Predicting Student Proficiency
Quelle	In: Asia Pacific Education Review, 13 (2012) 2, S.199-208 (10 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1598-1037
DOI	10.1007/s12564-011-9191-8
Schlagwörter	Statistical Analysis; Models; Probability; Longitudinal Studies; Academic Achievement; Scores; Exit Examinations; Urban Schools; Validity; Identification; At Risk Students; Educational Indicators; Federal Programs; Federal Legislation; California + Suchen Sie Ihr Suchwort? Statistische Analyse; Analogiemodell; Wahrscheinlichkeitsrechnung; Wahrscheinlichkeitstheorie; Longitudinal study; Longitudinal method; Longitudinal methods; Längsschnittuntersuchung; Schulleistung; Final examination; Abschlussprüfung; Urban area; Urban areas; School; Schools; Stadtregion; Stadt; Schule; Gültigkeit; Identifikation; Identifizierung; Educational indicato; Bildungsindikator; Bundesrecht; Kalifornien
Abstract	Value-added models and growth-based accountability aim to evaluate school's performance based on student growth in learning. The current focus is on linking the results from value-added models to the ones from growth-based accountability systems including Adequate Yearly Progress decisions mandated by No Child Left Behind. We present a new statistical approach that extends the current value-added modeling possibilities and focuses on using latent longitudinal growth curves to estimate the probabilities of students reaching proficiency. The aim is to utilize time-series measures of student achievement scores to estimate latent growth curves and use them as predictors of a dichotomous outcome, such as proficiency or passing a high-stakes exam, within a single multilevel longitudinal model. We illustrated this method through analyzing a three-year data set of longitudinal achievement scores and California High School Exit Exam scores from a large urban school district. This latent variable growth logistic model is useful for (1) early identification of students at risk of failing or of those who are most in need; (2) a validation or/and adequacy of student growth over years with relation to distal outcome criteria; (3) evaluation of a longitudinal intervention study. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10