Using Predictive Analytics: How Greenville College is Creating the Conditions for Student Success

  • 3 Min Read

To cultivate an environment where learners can thrive, institutions require innovative technology that will help create the conditions needed for them to succeed. The question I know you are probably asking yourself is—where do I start?

Are there easy wins for student success? Do simple and practical strategies exist to identify at-risk learners and help them stay on a successful path to graduation? At Greenville College, we think so — and it’s not as hard as you might think!

Focused on a way to use historical and current learning data to help identify which students are potentially at risk for dropping out, withdrawing, or failing altogether, Greenville College is using predictive analytics technology to dive deep into key achievement, engagement and completion data to get a new perspective of our learners’ progress and success. Our institution wanted a way to use our existing data to help us identify those students who might be struggling, much earlier in the year and more effectively than traditional methods had provided us.

As a Christian liberal arts college, we are committed to transforming lives and we want to do whatever we can to help each student be successful in his or her courses, stay in their program, and complete their degree. So, in the Fall of 2013, we began using the Desire2Learn Insights™ and Student Success System™ solutions to tap into our learning environment data and understand what was possible for predicting our students’ success.

Because the predictions in the Student Success System are based on how successful students were in historical courses using Desire2Learn Learning Environment, we began our validation by targeting primarily high-enrollment, freshmen courses. We also used the student grades and engagement information from the current courses where predictive modeling had been turned on. After some initial tweaking and adjustments, what we saw was remarkable — not just the impact of the predictions on student success but the valuable insights we gained about our existing procedures for at-risk interventions as well as our very own learning environment usage patterns.


In very short order, we were able to demonstrate the advantages of the Student Success System to our faculty and have begun developing a best practices protocol for using and engaging with the learning environment. Faculty immediately saw value in the success trending indicators (up and down arrows) most notably, in its at-a-glance ability to direct them to students declining in success. For those Instructors with fifty or more students in their class, a tool that will allow them to see students at risk sooner than they could normally identify was particularly exciting!
While faculty feedback of the Student Success System has been very positive—straightforward and user-friendly were common themes—we took the fall semester to develop our staff on the proper use of the tool and to increase our own understanding of the predictive modeling it provides. Because the data in this particular tool relies heavily on learning environment usage, the predictions are more accurate when the environment has been used consistently over multiple semesters by both learners and instructors. To that end, with the ease of implementation of the predictive tool, our 2014 focus is on rolling out the Student Success System to more courses under more Instructors so that we can continually refine what student success means across all programs at Greenville College. Additionally, we are also working on a beta implementation of a Student Success System component that taps into the data from our own student information system (SIS)—such as students’ GPA, ACT/SAT scores, etc.—so we can further tune or refine each individual student’s success index.

While it is still early days for Greenville College with this pioneering technology, the promise of predictive analytics to deliver earlier indicators of academic struggle than traditional methods is driving new opportunities for our faculty to understand the engagement, performance, and achievement of our learners. By recognizing students’ potential for success or failure early in a course, Instructors, Advisors, and other college support staff at Greenville Collage are given the precious gift of time—time to reach out and help struggling students find their way and improve their chances for success.

We are very excited to be a first adopter of the Desire2Learn Insights and Student Success System predictive analytics technology and we hope to share more of our story as it unfolds over the coming semesters.

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