Using Local Demographic Characteristics to Predict Admittance and Enrollment of Underrepresented Applicants in a Midwest Flagship University
Open Access
- Author:
- Ward, Melissa
- Graduate Program:
- Rural Sociology
- Degree:
- Master of Science
- Document Type:
- Master Thesis
- Date of Defense:
- March 14, 2016
- Committee Members:
- Kathryn Jo Brasier, Thesis Advisor/Co-Advisor
- Keywords:
- underrepresented
higher education
diversity
admittance
enrollment - Abstract:
- Colleges and universities have long touted the importance of diversifying their respective campuses, student bodies, as well as their faculty and staff. Even with these goals, an achievement gap exists between majority students (i.e. Caucasians) and students from underrepresented groups, such as certain racial/ethnic minorities, low socioeconomic status, and first-generation college students. In 2013, 40% of Caucasians between the ages of 25 and 29 had completed a Bachelor’s degree, whereas only 21% of African Americans and 16% of Hispanics of the same age range had achieved the same degree. Social and economic mobility is now largely dependent on the achievement of completing a post-secondary degree. Barriers to college admission drastically limit the ability of students within these underrepresented groups to attend institutions of higher education. With such disparities, there are opportunities for colleges to improve their recruitment of underrepresented students. In this study, Indiana University (IU) Office of Admissions’ undergraduate application data is analyzed with the applicant’s county and high school demographic characteristics. Logistic regression models are used to identify if the local demographic characteristics of an applicant’s county or high school predict if an applicant will be admitted to or enroll on campus. The likelihood of a person being admitted to and enrolling at IU changes based upon their type of underrepresentation and the spatial level of analysis. Improving the diversity of the student body on college campuses starts with understanding how local demographic characteristics are associated with the likelihood these underrepresented groups seek higher education. The thesis concludes by examining the implications of the analysis for recruiting and implementing targeted recruitment strategies based on this understanding of an applicant’s surroundings.