Date of Award


Document Type


Degree Name

Philosophy (Ph.D)


Education Specialties

First Advisor

Michael Sampson

Second Advisor

Joseph Rumenapp

Third Advisor

Richard Brown


There is a large achievement gap in literacy between Black and White students in the United States that has been found to be mostly due to both differing learning opportunities as well as to income levels. Meanwhile, much of the research on academic performance has focused on race with less attention on the income of the school neighborhood zip code as a mediating factor in test outcomes for racial/ethnic students. This research investigated trends in English Language Arts test scores compared to income in the surrounding communities among New York City schools’ racial/ethnic groups of middle school students; also, whether income discrepancies predict a gap in test scores of these groups. This study looked at ELA test scores for 8th grade middle school students from 2013 through 2019, grouped by demographics such as race/ethnicity, and income status. Disability status, English language skills, and gender were also described. The method employed was a non-experimental quantitative design with the generalized estimating equations (GEE) models. Sample size includes approximately 403 New York City schools per year. Publicly available data from the New York State Education Department were used for Grade 8 English Language Arts Assessment Data for seven years. GEE was utilized to test the relationships and hypothesis. Generalized estimating equations were fit with the mean scores as the dependent variable, and test year, student race, an indicator variable to distinguish between the 2013-2017 and 2018-2019 periods and a race by test year interaction term as covariates. The findings showed that all three variables were significantly associated with the 8th grade classroom ELA test score means. A generalized estimating equation approach was also used to capture the effect of schools on ELA test scores. These analyses showed that race/ethnicity, year, income, and the indicator variable described above are significantly associated with the ELA test scores.

Included in

Education Commons