Achievement gaps, the focus of this research, result from unequal achievement and the variance in achievement existing between different segments of the student population, for example, the difference in achievement between minority students and non-minority students. The No Child Left Behind Act of 2001 and AYP (Adequate Yearly Progress) focus on achievement gaps despite contradictory expressions about the efficacy of the act. The No Child Left Behind Act has created discussion and awareness of race, SES (economically advantaged and disadvantaged) and academic achievement.
There are conflicting beliefs about the impact of resources, funding and wealth on student achievement. This study explores those beliefs by reviewing related literature and obtaining data confirming relationships between district and locality indicators of wealth and funding and student achievement gaps in Virginia middle schools.
This study examines data from middle schools organized in the typical 6-8 grade, 6-7 grade and 7-8 grade design during the 2005-2006 school year. For each school, the researcher reviewed the percentage of students passing the Standards of Learning (SOL) assessments in English and math for the following student subgroups: White, Black, Latino, and economically advantaged and disadvantaged. Relationships between each of the six dependent variables and sixteen independent variables were determined using descriptive statistics and through multiple regression analyses.
Nine of the 16 independent variables had significant relationships with the selected dependent variables. The nine variables were: median family income, percentage of residents below the poverty line, percentage of residents identified as minority, percentage of core academic classes taught by highly qualified instructors, per pupil expenditure, student teacher ratio, percentage of renters, number of renters and percentage of students eligible for free and reduced-priced lunches.
The analysis acknowledged that relationships exist between wealth, funding and academic achievement gaps. Although conclusions about causality between or among the variables cannot be determined from this data, it is apparent that achievement gaps continue to be a subject requiring additional attention.
","abstract_html":"<p>Achievement gaps, the focus of this research, result from unequal achievement and the variance in achievement existing between different segments of the student population, for example, the difference in achievement between minority students and non-minority students. The No Child Left Behind Act of 2001 and AYP (Adequate Yearly Progress) focus on achievement gaps despite contradictory expressions about the efficacy of the act. The No Child Left Behind Act has created discussion and awareness of race, SES (economically advantaged and disadvantaged) and academic achievement.</p> <p>There are conflicting beliefs about the impact of resources, funding and wealth on student achievement. This study explores those beliefs by reviewing related literature and obtaining data confirming relationships between district and locality indicators of wealth and funding and student achievement gaps in Virginia middle schools.</p> <p>This study examines data from middle schools organized in the typical 6-8 grade, 6-7 grade and 7-8 grade design during the 2005-2006 school year. For each school, the researcher reviewed the percentage of students passing the Standards of Learning (SOL) assessments in English and math for the following student subgroups: White, Black, Latino, and economically advantaged and disadvantaged. Relationships between each of the six dependent variables and sixteen independent variables were determined using descriptive statistics and through multiple regression analyses.</p> <p>Nine of the 16 independent variables had significant relationships with the selected dependent variables. The nine variables were: median family income, percentage of residents below the poverty line, percentage of residents identified as minority, percentage of core academic classes taught by highly qualified instructors, per pupil expenditure, student teacher ratio, percentage of renters, number of renters and percentage of students eligible for free and reduced-priced lunches.</p> <p>The analysis acknowledged that relationships exist between wealth, funding and academic achievement gaps. Although conclusions about causality between or among the variables cannot be determined from this data, it is apparent that achievement gaps continue to be a subject requiring additional attention.</p>","abstract_has_math":false,"creators":["Richmond, Paulette Natasha"],"institution":null,"degree_name":"Doctor of Philosophy (PhD)","degree_level":"Dissertation","degree_discipline":null,"degree_department":null,"school":null,"contributors":["Stephen Tonelson","William Owings","John Nunnery"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2007,"date_issued":"2007-01-01T08:00:00Z","date_published":"2007-01-01T08:00:00Z","updated_at":"2026-07-24T03:35:08Z","subjects":["Achievement gap","Middle schools","Minority students","Virginia","Wealth","Educational Sociology","Secondary Education"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["9780549329695"],"render_values":[{"text":"9780549329695","href":null,"code":true}]}]},"links":{"outbound_url":"https://digitalcommons.odu.edu/urbanstudies_etds/12","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Stephen Tonelson","William Owings","John Nunnery"]},{"key":"dc:creator","label":"Author","values":["Richmond, Paulette Natasha"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2019-08-28T07:00:00Z"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy (PhD)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Achievement gap","Middle schools","Minority students","Virginia","Wealth","Educational Sociology","Secondary Education"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["9780549329695","https://digitalcommons.odu.edu/urbanstudies_etds/12"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Achievement gaps, the focus of this research, result from unequal achievement and the variance in achievement existing between different segments of the student population, for example, the difference in achievement between minority students and non-minority students. The No Child Left Behind Act of 2001 and AYP (Adequate Yearly Progress) focus on achievement gaps despite contradictory expressions about the efficacy of the act. The No Child Left Behind Act has created discussion and awareness of race, SES (economically advantaged and disadvantaged) and academic achievement.
There are conflicting beliefs about the impact of resources, funding and wealth on student achievement. This study explores those beliefs by reviewing related literature and obtaining data confirming relationships between district and locality indicators of wealth and funding and student achievement gaps in Virginia middle schools.
This study examines data from middle schools organized in the typical 6-8 grade, 6-7 grade and 7-8 grade design during the 2005-2006 school year. For each school, the researcher reviewed the percentage of students passing the Standards of Learning (SOL) assessments in English and math for the following student subgroups: White, Black, Latino, and economically advantaged and disadvantaged. Relationships between each of the six dependent variables and sixteen independent variables were determined using descriptive statistics and through multiple regression analyses.
Nine of the 16 independent variables had significant relationships with the selected dependent variables. The nine variables were: median family income, percentage of residents below the poverty line, percentage of residents identified as minority, percentage of core academic classes taught by highly qualified instructors, per pupil expenditure, student teacher ratio, percentage of renters, number of renters and percentage of students eligible for free and reduced-priced lunches.
The analysis acknowledged that relationships exist between wealth, funding and academic achievement gaps. Although conclusions about causality between or among the variables cannot be determined from this data, it is apparent that achievement gaps continue to be a subject requiring additional attention.
"]},{"key":"dc:title","label":"Title","values":["Wealth and Achievement Gaps: An Examination of Virginia Middle Schools"]}]}],"canonical_facts":{"dc:contributor":["Stephen Tonelson","William Owings","John Nunnery"],"dc:creator":["Richmond, Paulette Natasha"],"dc:date.available":["2019-08-28T07:00:00Z"],"dc:description.abstract":["Achievement gaps, the focus of this research, result from unequal achievement and the variance in achievement existing between different segments of the student population, for example, the difference in achievement between minority students and non-minority students. The No Child Left Behind Act of 2001 and AYP (Adequate Yearly Progress) focus on achievement gaps despite contradictory expressions about the efficacy of the act. The No Child Left Behind Act has created discussion and awareness of race, SES (economically advantaged and disadvantaged) and academic achievement.
There are conflicting beliefs about the impact of resources, funding and wealth on student achievement. This study explores those beliefs by reviewing related literature and obtaining data confirming relationships between district and locality indicators of wealth and funding and student achievement gaps in Virginia middle schools.
This study examines data from middle schools organized in the typical 6-8 grade, 6-7 grade and 7-8 grade design during the 2005-2006 school year. For each school, the researcher reviewed the percentage of students passing the Standards of Learning (SOL) assessments in English and math for the following student subgroups: White, Black, Latino, and economically advantaged and disadvantaged. Relationships between each of the six dependent variables and sixteen independent variables were determined using descriptive statistics and through multiple regression analyses.
Nine of the 16 independent variables had significant relationships with the selected dependent variables. The nine variables were: median family income, percentage of residents below the poverty line, percentage of residents identified as minority, percentage of core academic classes taught by highly qualified instructors, per pupil expenditure, student teacher ratio, percentage of renters, number of renters and percentage of students eligible for free and reduced-priced lunches.
The analysis acknowledged that relationships exist between wealth, funding and academic achievement gaps. Although conclusions about causality between or among the variables cannot be determined from this data, it is apparent that achievement gaps continue to be a subject requiring additional attention.
"],"dc:identifier":["9780549329695","https://digitalcommons.odu.edu/urbanstudies_etds/12"],"dc:subject":["Achievement gap","Middle schools","Minority students","Virginia","Wealth","Educational Sociology","Secondary Education"],"dc:title":["Wealth and Achievement Gaps: An Examination of Virginia Middle Schools"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Doctor of Philosophy (PhD)"]},"updated_at":"2026-07-24T03:35:08Z"}