Using data to improve retention

The University of Kentucky is making a major investment in data analytics to try to improve student retention. The approach is described in an article at Inside Higher Ed:

Every time students open the app to check their course schedule or the date for the next Wildcats game, they may be faced with a quick question: Have you bought all your textbooks already? Do you own a tablet? On a scale from one to five, how stressed are you?

The university collects a student’s responses to these kinds of questions on a per-student basis. To that record, they also add a student’s interactions with the campus LMS and participation in campus events, which are tracked through a card swipe-based attendance and incentive system.

All of these systems alone represent a big investment in tracking, but analytics is about doing something with all that data. UK has made a major push to make meaning from the data by hiring a team of 15 data analysts to develop and refine a predictive model of student engagement. The end goal is to increase retention rates which, assuming they’re even marginally successful, will more than pay for the investment in all the staff and databases.

Here’s how:

  • The cost of attendance in-state is about $20,000, and $30,000 for out-of-state (source)
  • The average financial aid award is about $10,000
  • So net revenue per student is about $10,000-$20,000 (assuming in-state students); let’s call it $15,000 for simplicity’s sake.
  • The freshman enrollment was about 4300 students
  • A 1% increase in retention is 43 students
  • 43 × $15,000 = $645,000 additional revenue
  • $645,000 × 4 yrs = $2,580,000
  • $2,580,000 ÷ 15 staff = $172,000 per additional staff line

And that’s making very conservative estimates throughout. That’s also not including the cost savings on the enrollment side of not needing to recruit as large a class.

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