Understanding Graduation Rates at Higher Education Institutions:
A Forecasting Model
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Serina Al‐Haddad
School of Business Administration Stetson University Rachael Boone School of Business Administration Stetson University Emma Campbell School of Business Administration Stetson University Corresponding Author: Serina Al‐Haddad, Shaddad1@stetson.edu |
ABSTRACT
Graduation rates and degree completion have always been a concern for students, students’ families and universities. Moreover, many consider college degree completion rates to be among one of the most important indicators of institutional quality according to a report from the Higher Education Research Institute published in the United States of America. This research studied factors that can explain graduation rates which include student‐faculty ratio, financial factors, and enrollment status. Data was collected and analyzed for state and private universities, and a Multiple Regression Model (MLR) was built to forecast graduation rates. The model was able to highlight variables that significantly relate to graduation rates. Researchers can use this article to understand the different factors that correlate with degree completion and to forecast graduations rates at Higher Education Institutions. The international researcher can explore replicating the forecasting model at universities outside the United States of America.
Keywords: graduation rates, degree completion, institutional quality
Graduation rates and degree completion have always been a concern for students, students’ families and universities. Moreover, many consider college degree completion rates to be among one of the most important indicators of institutional quality according to a report from the Higher Education Research Institute published in the United States of America. This research studied factors that can explain graduation rates which include student‐faculty ratio, financial factors, and enrollment status. Data was collected and analyzed for state and private universities, and a Multiple Regression Model (MLR) was built to forecast graduation rates. The model was able to highlight variables that significantly relate to graduation rates. Researchers can use this article to understand the different factors that correlate with degree completion and to forecast graduations rates at Higher Education Institutions. The international researcher can explore replicating the forecasting model at universities outside the United States of America.
Keywords: graduation rates, degree completion, institutional quality
Preferred Citation:
Al-Haddad, S., Boone, R., and Campbell, E. (2018). Understanding graduation rates at higher education institutions: A forecasting model. International Journal for Business Education, 158, p. 10-23.
Al-Haddad, S., Boone, R., and Campbell, E. (2018). Understanding graduation rates at higher education institutions: A forecasting model. International Journal for Business Education, 158, p. 10-23.
