OPAIR supports University enrollment modeling efforts

Sep 8, 2022

In 2019, Penn State leadership was searching for a way to better identify factors influencing an individual’s decision to enroll at the University and why students are successful and ultimately earn their degree from Penn State. A more robust enrollment and retention model was sought to predict student enrollment and retention rates better and enhance applicable data-informed decisions. Soon after, an enrollment modeling task force was created from Penn State representatives across various departments University-wide. A team from the Office of Planning, Assessment, and Institutional Research (OPAIR) was then assembled to begin work on the project.

A pilot model utilizing individual student-level data was created, with data points beginning in high school before a student enters college. Once enrolled, the data points track the student’s engagement and academic progress over time to best predict if the student will remain at Penn State.

“Having the ability to view data that gauge students’ specific interests and level of engagement with the University and one another will give us more detailed insight on what brought them to Penn State and what is or isn’t keeping them here,” said Carly Sunseri, director of data science for OPAIR.

The team is currently working on better understanding the factors with the highest predictability rate when it comes to retention. With a project plan in place through the end of 2022, the team has continued to add sources and columns to data sets, and as more data is available this fall, they’ll be able to judge how the model is working. The goal is for the additional data to assist with updated modeling for fall 2023 projections and give a better idea of the “why” behind the numbers.

“Our hope is that this model will give University leadership a much clearer picture of our current enrollment and retention standing and ways we can continue to improve in these areas. We’re optimistic this tool will significantly expand the availability of relevant data to better inform decision making across the institution,” said Sunseri.