Date of Award

Summer 7-30-2021

Degree Type


Degree Name

EdS Education Leadership Management and Policy


Education Leadership, Management and Policy


Jan Furman, Ed.D.

Committee Member

Monica Browne

Committee Member

Rong Chen, Ph.D.

Committee Member

Chris Irving, Ed.D.

Committee Member

Joseph S. Fulmore, Sr, Ed.D.


student factors, Regional Achievement Centers, Priority schools, student Achievement


The purpose of this quantitative predictive analysis study was to identity what student characteristics such as subgroups’ gender, ELL, race/ethnicity, more specifically Black and Latino, are important in predicting student achievement in two Priority schools in their final year of Regional Achievement Center (RAC) delivery and support to these schools, as measured by Language Arts PARCC 2017–2018 for 6th, 7th, and 8th-grade scores. Regional Achievement Centers (RACs) were instituted as a reform method to support New Jersey’s efforts to improve low-performing schools. The New Jersey Department of Education defined these schools as Priority, with the lowest-performing student achievement and graduation rates among subgroups. RACs instituted eight turnaround principles aimed to advance low-performing schools. The research question for this study was: What is the Relationship Between Student Factors and Middle School Student Achievement? To answer this question, descriptive statistics were first used to identify measures of central tendencies in the study. The empirical data was examined to determine if student factors as in gender, race/ethnicity (Blacks and Hispanics), ELL, and grade levels, can predict student achievement in two urban Priority schools in Passaic County, New Jersey. This public data was procured from the New Jersey School Performance Reports, school websites, and personnel. This study utilized a quantitative predictive analysis using descriptive statistics. Multiple linear regression was used to assess if the independent variable (student factors, gender, race/ethnicity (Blacks and Hispanics), ELL, and grade levels) predicted the dependent variable (student achievement, as measured by ELA PARCC 2017–2018 for 6th, 7th, and 8th-grade scores).