Data comes in all shapes and sizes, and while the saying “go big or go home” might have some educators thinking that “big data” is the only way to go. But it’s simply not true. Equally important in your institution’s retention efforts is “small data” – the information that you likely already collect, telling you on a daily basis how engaged a student is at any given moment.
Both big and small data empower you to not only understand your students – their challenges and their successes – but when combined, these data sets give you the insight to know exactly when and how to reach out so you can retain more students.
Let’s take a closer look.
Big data interventions help your team discover correlations between student information and student behavior. This information is often based on a student’s historical and personal profile. Using big data, you can predict and tag at-risk students so you are not only on the lookout for potential problem areas, you can be proactive and reach out before those problem areas even surface. Big data modeling should incorporate:
- Prior academic data
- Life events
- Financial aid information
- Registration data
Small data interventions, on the other hand, might not help you assess the big picture quite like big data, but it can be even more important when it comes to targeting and supporting at-risk students. Small data gives you a snapshot of a students’ current progress so you can see exactly where a student might be falling behind. Small data modeling should incorporate:
- Academic performance
- Classroom attendance
- Course management software usage
The power of your retention strategy comes in finding correlations between all of this student information and how your students actually persist – connecting data between systems and creating predictive models based upon the insights gathered.