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A Longitudinal Investigation of Lang...

Marquez, Jocabed G.

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A Longitudinal Investigation of Language and Executive Function on Mathematics and Science Achievement in Early Childhood.

Record Type:	Electronic resources : Monograph/item
Title/Author:	A Longitudinal Investigation of Language and Executive Function on Mathematics and Science Achievement in Early Childhood./
Author:	Marquez, Jocabed G.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2018,
Description:	190 p.
Notes:	Source: Dissertation Abstracts International, Volume: 80-01(E), Section: A.
Contained By:	Dissertation Abstracts International80-01A(E).
Subject:	Early childhood education. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10985635
ISBN:	9780438396159

A Longitudinal Investigation of Language and Executive Function on Mathematics and Science Achievement in Early Childhood.
Marquez, Jocabed G.

A Longitudinal Investigation of Language and Executive Function on Mathematics and Science Achievement in Early Childhood. - Ann Arbor : ProQuest Dissertations & Theses, 2018 - 190 p.

Source: Dissertation Abstracts International, Volume: 80-01(E), Section: A.

Thesis (Ph.D.)--Texas State University - San Marcos, 2018.

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.

ISBN: 9780438396159Subjects--Topical Terms:

518817
Early childhood education.

A Longitudinal Investigation of Language and Executive Function on Mathematics and Science Achievement in Early Childhood.
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500 $a Source: Dissertation Abstracts International, Volume: 80-01(E), Section: A.
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520 $a 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.
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