Incorporating Student Mobility in Studying Academic Growth in Math: Comparing Several Alternative Multilevel Formulations

Autor/inn/en	Heck, Ronald H.; Reid, Tingting; Leckie, George
Titel	Incorporating Student Mobility in Studying Academic Growth in Math: Comparing Several Alternative Multilevel Formulations
Quelle	In: School Effectiveness and School Improvement, 33 (2022) 4, S.516-543 (28 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Heck, Ronald H.) ORCID (Reid, Tingting) ORCID (Leckie, George)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0924-3453
DOI	10.1080/09243453.2022.2060265
Schlagwörter	Student Mobility; Mathematics Achievement; Growth Models; Educational Improvement; Kindergarten; Grade 1; Grade 2; Grade 3; Grade 4; Elementary Education; Student Characteristics; Institutional Characteristics; Early Childhood Longitudinal Survey + Suchen Sie Ihr Suchwort? Student; Students; Mobility; Schüler; Schülerin; Studentin; Mobilität; Mathmatics sikills; Mathmatics achievement; Mathematical ability; Mathematische Kompetenz; Teaching improvement; Unterrichtsentwicklung; School year 01; 1. Schuljahr; Schuljahr 01; School year 02; 2. Schuljahr; Schuljahr 02; School year 03; 3. Schuljahr; Schuljahr 03; School year 04; 4. Schuljahr; Schuljahr 04; Elementarunterricht
Abstract	Increasing pupil mobility has led to widespread concern among parents, educators, and policymakers regarding its negative effects on academic performance. An important issue in examining mobility effects in longitudinal school achievement comparisons is providing accurate estimates. The presence of pupil mobility suggests that we should model pupils as belonging to the series of schools attended and not just their first or final school. We discuss several challenges in accounting for student mobility and, because of the presence of mobile pupils, how to represent the contribution of multiple schools attended on estimating academic growth properly. We then contrast several previous longitudinal multilevel models utilized with two cross-classified multiple membership (CCMM) models, which have been proposed to cumulate annual school effects on pupils' academic growth better given the complexity of the multilevel data structure. We discuss our results in terms of their theoretical and practical implications for research on school academic improvement. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01