As a student, choosing a college is a significant decision that has a lifelong impact, personally and professionally. Many factors come into play: the campus experience, available academic programs, cost, sports and athletic opportunities, residences, and word-of-mouth referrals.

Once a selection is made and the student enrolls, many of these same factors will also determine how students perceive their college experience. Living conditions, their roommate, how they finance their education, the groups they’re involved in, and the friends they meet, all shape student success—and that’s a perennial challenge for administrators charged with improving retention rates.

Uncovering retention insights with big data
As vice president for academic administration at Gannon University in Erie, Pennsylvania, making sense of the vast array of data that we know about students is critical to our objective of closing the student retention gap and developing programs that provide encouragement, coaching, and advice to those who exhibit the earliest signs of dropout risk.

But, tracking a student’s engagement, academic record, and financial status is an intricate and complex task. Following numbers on a spreadsheet is manageable if you’re tracking a single factor, such as academic scores, but when multiple factors come into play, insights are hard to glean.

Find out how Gannon University improved student retention by 5 percent #highered

Gannon’s philosophy is that we want each student to be successful. Retention metrics are important, and ours have always been comparable with our peers, but several years ago we decided that’s not good enough. We constantly strive to deliver a memorable and successful university experience for each student. Data is key to helping us achieve that mission, but we knew that to truly understand the reasons students leave our school, we needed to find a way to visualize that data in more useful, comprehensive contexts than a spreadsheet or other systems allow.

With this in mind, we set about developing a predictive model using a pioneering technology known as glyphs.

Predicting student retention with glyphs
Glyph-based data visualization is based on two decades of research into how the mind works to understand the world around it. Instead of looking at a field in a spreadsheet or a static chart, glyphs are a visualization of all the data available on a student including financial aid, recruiting, admissions, academic, and extracurricular data within a single multi-dimensional, interactive view. A combination of color-coded shapes, of varying sizes, gives us a full picture so we can clearly see retention risks and discover new insights.

About the Author:

Dr. Steven A. Mauro is vice president of academic administration at Gannon University in Pennsylvania. He is also an adjunct lecturer in the biology department and for academic support programs.


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