NEIGHBORHOOD CONDITIONS IN RELATION TO ACADEMIC ACHIEVEMENT OF ELEMENTARY SCHOOL STUDENTS
1 online resource (153 pages) : PDF
University of North Carolina at Charlotte
In the United States, the academic achievement gap between European American and African American students has been identified as one of the major problems related to educational equity. Students’ academic achievement has been largely examined from aspects related to student characteristics, student family background, teacher quality, parental involvement, and school features (Anderman & Anderman, 1999; Caprara, Barbaranelli, Steca, & Malone, 2006; Keith, Keith, Troutman, & Bickley, 1993; Meece & Holt, 1993; Paulson, 1994; Staub & Stern, 2002). However, the relationship between neighborhood and academic achievement has received inadequate attention overall. Furthermore, most neighborhood-academic achievement studies failed to consider the spatial properties of neighborhood attributes. The present study investigated relationships between neighborhood conditions and academic achievement of elementary school students with modeling spatial dependencies of neighborhood attributes. Measures of neighborhood conditions were developed through Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA). Then a geodatabase was built to integrate neighborhood attributes and school characteristics. Exploratory Spatial Data Analysis (ESDA) was used to explore the spatial variations of neighborhood-based regional attributes present within Charlotte-Mecklenburg Schools (CMS) area. Finally, a transformed two-level Hierarchical Linear Modeling (HLM) with modeling spatial dependencies was used to investigate relationships between neighborhood conditions and academic achievement of elementary school students. One of the major findings from the current study is that school environments have a close association with mathematics achievement especially for students living in disadvantaged neighborhoods with more risk factors.
Academic Achievement GapNeighborhood ConditionSpatial Autocorrelation
Lambert, RichardTang, WenwuPolly, Drew
Thesis (D.Ed.)--University of North Carolina at Charlotte, 2017.
This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s). For additional information, see http://rightsstatements.org/page/InC/1.0/.
Copyright is held by the author unless otherwise indicated.