College Enrollment Trends and Pattern Evaluation “A Data Analytics Investigation”

Abstract

The U.S. higher education system is known for its diversity and independence. The successful completion of higher education is seen as an essential parameter for student accomplishment and economic progress. Demographics influence a student’s everyday life. A student’s socioeconomic status, family structure, parent level of education, culture, technology usage, transience, race, spirituality, and crime rate near the home all impact them daily (VanderStel, 2014). Demographics have a significant influence on educational access and equity; thus, researchers, educators, and practitioners require better knowledge of demographics and its impact on student enrollment in colleges of engineering.The present study begins with an overview of early models, dealing with undergraduate enrollment, retention, and graduation at a public university. The study data includes student-level enrollment and demographics data from 2015 to 2019 for those enrolled (n= 9034 students) and Zip Code level U.S. Census data collected during the year 2017. The study followed a sequential research design that included QGIS Mapping, Spearman Correlation analysis, cluster analysis, and control group analysis in determining the main factors for student enrollment decisions/trends and identifying those Zip Codes which fit characteristics for a strong recruitment region but attracted fewer students than estimated. The research aims to identify factors that characterize Zip Codes in the universities draw area within which it could recruit more students and identify those Zip Codes which behave abnormally and use additional research to attract, engage, and retain students. The findings provide evidence that Zip Code level demographic attributes such as minority population, internet access, travel distance, educational level, total population, and college eligible population contribute to students’ enrollment decisions. These factors provide the researchers with additional insights into the community characteristics that admitted students represent. Furthermore, out of 269 Zip Codes,10 Zip Codes showed abnormality of low student enrollment count despite achieving the highest level of performance in demographic characteristics. This research is a starting point to study and recognize the economic limitations faced by the students of specific Zip Codes and assist University administrators and policymakers in formulating strategies to attract and enroll more students.