White Students in Urban Schools: The Unheard Voice in the Achievement Gap
type: CreativeWork
description: This study analyzes the academic performance of White students in urban settings, relative to Minority peers, and investigates structural variables that might exacerbate or attenuate differences. The investigation is motivated by and extends qualitative work investigating the experiences of middle school students in Texas (Morris, 2006). Research on the academic achievement of impoverished urban White students is limited. The present study investigates achievement gaps that are probably a function of student demographic characteristics, and achievement equity (i.e., the influence of school-level demographic and structural characteristics on student achievement and on distributions of student achievement among schools). The use of a multilevel regression model is appropriate for this type of study. The OAT data used in this study are hierarchical in nature because students are nested within schools. The use of a multi-level model (MLM) addresses the challenge of students nested within schools. The predictor variables of Ethnicity and Poverty exhibit a strong relationship with achievement linked to both of the dependent variables of reading and math. The analysis showed a significant relationship as evidenced by student Poverty was -9.42 for reading and -7.63 for math representing the average decrease in score for impoverished students from the average mean score. Ethnicity predictor variable showed the mean score for Minority students in math was 15.54 points lower than for White students and the reading for Minority students was 9.84 points lower than for White students. The gap for impoverished White is larger than for economically disadvantaged Minority (7.34 points more than for economically disadvantaged Minority students- 22.41 points to 15.07 points) in the dependent variable of reading. This finding is consistent for the dependent variable of math also: the gap for economically disadvantaged White is larger than for impoverished Minority (6.59 points larger t…
abstract: This study analyzes the academic performance of White students in urban settings, relative to Minority peers, and investigates structural variables that might exacerbate or attenuate differences. The investigation is motivated by and extends qualitative work investigating the experiences of middle school students in Texas (Morris, 2006). Research on the academic achievement of impoverished urban White students is limited. The present study investigates achievement gaps that are probably a function of student demographic characteristics, and achievement equity (i.e., the influence of school-level demographic and structural characteristics on student achievement and on distributions of student achievement among schools). The use of a multilevel regression model is appropriate for this type of study. The OAT data used in this study are hierarchical in nature because students are nested within schools. The use of a multi-level model (MLM) addresses the challenge of students nested within schools. The predictor variables of Ethnicity and Poverty exhibit a strong relationship with achievement linked to both of the dependent variables of reading and math. The analysis showed a significant relationship as evidenced by student Poverty was -9.42 for reading and -7.63 for math representing the average decrease in score for impoverished students from the average mean score. Ethnicity predictor variable showed the mean score for Minority students in math was 15.54 points lower than for White students and the reading for Minority students was 9.84 points lower than for White students. The gap for impoverished White is larger than for economically disadvantaged Minority (7.34 points more than for economically disadvantaged Minority students- 22.41 points to 15.07 points) in the dependent variable of reading. This finding is consistent for the dependent variable of math also: the gap for economically disadvantaged White is larger than for impoverished Minority (6.59 points larger t…
author: Brady, Christopher E.
language: English
keywords: Education, Educational Leadership, Educational Theory, Education Policy, Achievement Gaps, White Poverty, Urban Schools, Hierarchical Linear Modeling (HLM)
date published: 2013-06-07
date modified: 2026-07-24T03:37:01Z
provider: OhioLINK
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: Ohio University