Date of Graduation

5-2025

Degree Type

Dissertation/Thesis

Degree Name

Bachelor of Science (BS)

Major

Computer Science

Advisor(s)

Gregory Donovan

Abstract

The COVID-19 pandemic triggered widespread disruptions to student learning across the United States, intensifying many pre-existing educational inequalities. This study investigates how public health conditions, environmental factors, and federal stimulus funding shaped pandemic high school outcomes in New York City, one of the nation’s largest and most diverse school districts. Using open-access datasets from city agencies, this analysis examines the relationships between local COVID-19 severity, air pollution exposure, budget allocations, and student success, as measured by attendance and graduation rates. Findings reveal that while local COVID-19 rates and air quality conditions varied across boroughs, they did not consistently predict educational outcomes. Instead, broader socioeconomic disparities, technological access, and school-level resource deployment arose as stronger influences on student trajectories. Federal pandemic relief funding contributed to modest improvements in some boroughs, but its impact varied widely, underscoring that strategic, equity-focused interventions are essential for long-term recovery. The study highlights the potential and limitations of public open-access data to illuminate structural educational inequalities and inform more resilient and equitable future policies.

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