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Autor/in | Marquez, Jocabed G. |
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Titel | A Longitudinal Investigation of Language and Executive Function on Mathematics and Science Achievement in Early Childhood |
Quelle | (2018), (190 Seiten)
PDF als Volltext Ph.D. Dissertation, Texas State University - San Marcos |
Sprache | englisch |
Dokumenttyp | gedruckt; online; Monographie |
ISBN | 978-0-4383-9615-9 |
Schlagwörter | Hochschulschrift; Dissertation; Longitudinal Studies; Executive Function; Mathematics Achievement; Science Achievement; Early Childhood Education; Language Proficiency; Spanish Speaking; Kindergarten; Grade 1; Grade 2; Growth Models; Scores; Multivariate Analysis; Predictor Variables; Structural Equation Models; Children; Surveys; Early Childhood Longitudinal Survey Thesis; Dissertations; Academic thesis; Longitudinal study; Longitudinal method; Longitudinal methods; Längsschnittuntersuchung; Mathmatics sikills; Mathmatics achievement; Mathematical ability; Mathematische Kompetenz; Early childhood; Education; Frühkindliche Bildung; Frühpädagogik; Language skill; Language skills; Sprachkompetenz; School year 01; 1. Schuljahr; Schuljahr 01; School year 02; 2. Schuljahr; Schuljahr 02; Multivariate Analyse; Prädiktor; Child; Kind; Kinder; Survey; Umfrage; Befragung |
Abstract | The United States faces high demand for science, technology, engineering, or mathematics (STEM) professionals and a scarce supply of individuals who pursue STEM careers, especially minority populations in the U.S with proficiency in a language other than English. The primary goal of this research was to determine the impact of use of Spanish in the home and direct cognitive assessments (executive function) on student achievement in mathematics and science during the fall of kindergarten, spring kindergarten, fall and spring of first grade, and fall of second grade. Parallel process longitudinal growth modeling was used to examine mathematics and science trajectories over time in a large cohort of students while simultaneously investigating tangential issues affecting change in achievement over time. Several analyses were employed in this study with the goals of: (1) Examining the growth of mathematics or science scores in isolation employing a univariate analysis model within the PPLGM, (2) Revealing the joint associations between growth factors capturing mathematics and science achievement employing an unconditional multivariate analysis and (3) Examining the effect of time-varying covariates as predictors of mathematics achievement scores at each year by employing a conditional multivariate analysis. Structural equation modeling (SEM) served as the analytic framework for conducting all analyses. This study used variables from the Early Childhood Longitudinal Study Cohort 2011 sponsored by the National Center for Education Statistics (NCES), within the U.S. Department of Education's Institute of Education Sciences. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.] (As Provided). |
Anmerkungen | ProQuest LLC. 789 East Eisenhower Parkway, P.O. Box 1346, Ann Arbor, MI 48106. Tel: 800-521-0600; Web site: http://www.proquest.com/en-US/products/dissertations/individuals.shtml |
Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
Update | 2020/1/01 |