Date of Award

Fall 9-12-2018

Degree Type

Dissertation

Degree Name

EdD Education Leadership, Management and Policy

Department

Education Leadership, Management and Policy

Advisor

Gerard Babo, Ed.D

Committee Member

Christopher Tienken, Ed.D

Committee Member

Michael Kuchar, Ph.D

Keywords

PARCC, standardized test, student achievement, school finance, technology budget

Abstract

The purpose of this relational, nonexperimental, explanatory, cross-sectional study with quantitative methods was to explain the relationship, if any, between the administrative information technology budget as a proportion of the overall undistributed expenditure account on PK-12 and K-12 New Jersey public school districts’ student achievement in English language arts (ELA) and mathematics, as measured by the high-stakes New Jersey standardized test entitled Partnership for Assessment of Readiness for College and Careers (PARCC), during the 2016–2017 school year. The administrative information technology budget refers to networking, technology infrastructure, and support, rather than hardware. Additionally, the study included examination of the influence of other student, district, and staff variables such as student absenteeism, percentage of students with disabilities, socioeconomic status, district enrollment size, percentage of faculty with advanced degrees, and faculty attendance on the PARCC 2016– 2017 in both ELA and mathematics.

The target variable of interest, the administrative information technology budget as proportion of the overall undistributed expenditure account, was not found to be a significant predictor of achievement on PK-12 or K-12 New Jersey school districts PARCC scores in ELA or mathematics.The results of this study indicated that no statistically significant relationship exists between the proportion of the administrative information technology budget and proficiency percentages on PK-12 or K-12 New Jersey school districts PARCC scores in ELA or mathematics. Of the variables included in this study, student absenteeism, percentage of faculty with advanced degrees, and enrollment size were deemed statistically significant predictors when PARCC ELA was the dependent variable. When PARCC mathematics was the dependent variable, student absenteeism and socioeconomic status were the identified statistically significant predictor variables.

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