Online Program

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Wednesday, May 29
Data Visualization
Computational Statistics
Machine Learning
Opening Mixer & E-Posters
Wed, May 29, 5:30 PM - 7:00 PM
Grand Ballroom Foyer

Using Data Science to Support Enrollment Decisions in Higher Education (306265)

*Monica M King, Drexel University 

Keywords: higher education, enrollment management, college admissions, ensemble models, predictive models

Higher education institutions rely on strategic enrollment management to manage enrollment outcomes, meet revenue and institutional goals, and support student success. At a time when the average number of college applications per student is increasing, enrollment management practitioners are navigating with greater uncertainty while facing the pressures of an increasingly competitive market. At the same time, in a world where more data are generated and collected, college and universities have more information at their disposal to make more precise and timely decisions.

Drexel University is a private research university in Philadelphia, PA that currently enrolls nearly 25,000 undergraduate and graduate students. The Enrollment Analytics team at Drexel University leverages data science to support strategic enrollment management to recruit right-fit students and support them to be successful. This presentation focuses on Enrollment Analytics’ core process of projecting freshman enrollment throughout the freshman admissions cycle and in determining financial aid awards. We describe our ensemble modeling approach, show how student data are incorporated in an ethical manner, and provide implications for strategic decision-making as enrollment projections change over time.