Disciplines
Applied Mathematics | Applied Statistics | Categorical Data Analysis | Higher Education | Institutional and Historical
Abstract (300 words maximum)
University education can lead to upward income mobility for low-income students. Being exposed to other student’s life experiences that are different from their own may highlight activities and actions that they may want to consider aiding their success. According to the U.S. Bureau of Labor Statistics, the median weekly earnings in 2019 for all workers in the U.S. was $969. Of those, U.S. workers who held bachelor’s degrees earned $1,248. In 2016, the Brookings Institute found that Pell Grant recipients and first-generation student loan borrowers attended universities that had lower graduation rates and higher loan default rates in comparison to other loan borrowers.
Using hypothesis tests including t-test, simple linear regression, chi-square analyses, among others, this researcher seeks to investigate relationships that may alert the reader to the needs of Pell Grant recipients and first-generation students at post-secondary institutions. For example, do Pell Grant recipients and first-generation students have lower graduation rates and higher loan default rates even at the same university? The goal is to increase graduation rates and decrease loan default rates while also enabling Pell grant recipients to leave with the least amount of debt.
The College Scorecard dataset includes demographics of schools serving low-income students including Title IV participation status, the percentage of undergraduate Pell recipients, being a 2-year or 4-year institution, public or private ownership of the institution, whether the university awards Associate’s, Bachelor’s, or Graduate degrees, the proportion of STEM-focused majors, the net revenue per full-time student, the instructional expenditures per full-time student, the proportion of full-time faculty, and the average faculty salary. Through analyzing these variables, the reader can gain insight into the possible non-academic needs of Pell Grant recipients and first-generation students.
Academic department under which the project should be listed
CCSE - Data Science and Analytics
Primary Investigator (PI) Name
Susan Mathews Hardy
Included in
Applied Mathematics Commons, Applied Statistics Commons, Categorical Data Analysis Commons, Higher Education Commons, Institutional and Historical Commons
Access to Higher Education: Do schools “grant” success?
University education can lead to upward income mobility for low-income students. Being exposed to other student’s life experiences that are different from their own may highlight activities and actions that they may want to consider aiding their success. According to the U.S. Bureau of Labor Statistics, the median weekly earnings in 2019 for all workers in the U.S. was $969. Of those, U.S. workers who held bachelor’s degrees earned $1,248. In 2016, the Brookings Institute found that Pell Grant recipients and first-generation student loan borrowers attended universities that had lower graduation rates and higher loan default rates in comparison to other loan borrowers.
Using hypothesis tests including t-test, simple linear regression, chi-square analyses, among others, this researcher seeks to investigate relationships that may alert the reader to the needs of Pell Grant recipients and first-generation students at post-secondary institutions. For example, do Pell Grant recipients and first-generation students have lower graduation rates and higher loan default rates even at the same university? The goal is to increase graduation rates and decrease loan default rates while also enabling Pell grant recipients to leave with the least amount of debt.
The College Scorecard dataset includes demographics of schools serving low-income students including Title IV participation status, the percentage of undergraduate Pell recipients, being a 2-year or 4-year institution, public or private ownership of the institution, whether the university awards Associate’s, Bachelor’s, or Graduate degrees, the proportion of STEM-focused majors, the net revenue per full-time student, the instructional expenditures per full-time student, the proportion of full-time faculty, and the average faculty salary. Through analyzing these variables, the reader can gain insight into the possible non-academic needs of Pell Grant recipients and first-generation students.