Data Science to Identify Inequalities in CPS

Session Number

BVHSO 07

Advisor(s)

Angel Alvarez, Northwestern University, Feinberg School of Medicine

Discipline

Behavioral and Social Sciences

Start Date

17-4-2024 11:05 AM

End Date

17-4-2024 11:20 AM

Abstract

This project aims to investigate and identify the disparities in resource allocation across Chicago's Public School System. Leveraging an array of data science tools including Microsoft Excel functions, Python, and Jupyter Notebook, we have conducted comprehensive analyses. Our data derives from publicly accessible datasets obtained through the Freedom of Information Act (FOIA) from CPS and the Illinois State Board of Education, encompassing transfer records, student performance metrics, budget records, and selective enrollment test scores. Additionally, we incorporate FOIA records from the Illinois District Attorney’s office to scrutinize the processing of these records. We also utilize web scraping of websites to gather further data. Through our analyses, stark inequities emerge among schools and neighborhoods within the Chicago area. By presenting these findings and associated trends at board meetings, we aim to advocate for and enact reforms that foster a more just and equitable educational landscape for all students.

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Apr 17th, 11:05 AM Apr 17th, 11:20 AM

Data Science to Identify Inequalities in CPS

This project aims to investigate and identify the disparities in resource allocation across Chicago's Public School System. Leveraging an array of data science tools including Microsoft Excel functions, Python, and Jupyter Notebook, we have conducted comprehensive analyses. Our data derives from publicly accessible datasets obtained through the Freedom of Information Act (FOIA) from CPS and the Illinois State Board of Education, encompassing transfer records, student performance metrics, budget records, and selective enrollment test scores. Additionally, we incorporate FOIA records from the Illinois District Attorney’s office to scrutinize the processing of these records. We also utilize web scraping of websites to gather further data. Through our analyses, stark inequities emerge among schools and neighborhoods within the Chicago area. By presenting these findings and associated trends at board meetings, we aim to advocate for and enact reforms that foster a more just and equitable educational landscape for all students.