TITLE:
Managing Factors That Correlate to High Cohort Default Rate at Public 2-Year Community Colleges in Michigan
AUTHORS:
Emmanuel Obilor Njoku
KEYWORDS:
Michigan, Student Loan Debt, National Data, Federal Financial Aid, Variables Affecting Student Loan Default, Repayment, Age, Gender, Ethnicity/Race
JOURNAL NAME:
Journal of Financial Risk Management,
Vol.12 No.4,
December
5,
2023
ABSTRACT: Community colleges serve
more than a considerable proportion of Americans who could not otherwise attend
colleges by providing access to fulfill their educational goals. Many of the
students enrolled in the institutions look to the federal government to finance their educational expenses by obtaining
federally guaranteed student loans. The borrowers who default on their student
loans cut across race, gender, and age, with Blacks and Hispanic American males more likely to default. The research
problem addressed in this quantitative
correlational study was the high cohort default rates at 26 public 2-year community colleges in Michigan. The high cohort default rates present
problems to the institutions’ ability to generate revenue to meet educational
budgets. The purpose of this quantitative correlational study was to identify
variables associated with student loan default in the 26 public 2-year
community colleges in Michigan. The study was guided by the conceptual
framework of the student-institution fit model, focusing on individual student
attributes and institution-level variables that accounted for the willingness
to repay behavior. A quantitative methodology with a nonexperimental design was
used to address the research questions.
Secondary data were extracted from the National Student Loan Data System and the
Integrated Postsecondary Education Data
System. The results for all the research questions showed that the assumptions
of normality, homoscedasticity, and absence of multicollinearity tests were
met, and null hypotheses were not rejected. The study’s findings showed that
institution-level factors did not significantly predict student loan default among borrowers but rather individual
characteristics. I recommended future research to explore default
patterns among borrowers in public 2-year community colleges after the COVID-19
crisis in terms of federal government policies that could result in a
recommendation for practice for institutions. The practice recommendations
included institutions developing a financial aid education and outreach
program, a default prevention guide, and special attention to students eligible
for Pell Grants.