Enrollment Projection Using Markov Chains: Detecting Leaky Pipes and the Bulge in the Boa

Rex Gandy, Lynne Crosby, Andrew Luna, Daniel Kasper, Sherry Kendrick
https://doi.org/10.34315/apf1472019

Abstract

While Markov chains are widely used in business and industry, they are used within higher education only sporadically. Furthermore, when used to predict enrollment progression, most of these models use student level as the classification variable. This study uses grouped earned student credit hours to track the movement of students from one academic term to the other to better identify where students enter or leave the institution. Results from this study indicate a high level of predictability from one year to the next. In addition, the use of the credit hour flow matrix can aid administrators in identifying trends and anomalies within the institution’s enrollment management process.

Keywords: Markov chains, enrollment projections, enrollment management, enrollment trends, enrollment

Additional Information

Authors

Rex Gandy, Austin Peay State University

Lynne Crosby, Austin Peay State University

Andrew Luna, Austin Peay State University

Daniel Kasper, Austin Peay State University

Sherry Kendrick, Austin Peay State University