2. Predicting Student Enrollment

3. Confessions – Part 1 There are no easy buttons
I am not a data scientist
What worked for us may not work for you

5. Pre-enrollment behavior
Matriculated as Freshmen, average transfer credits, last 12 years

6. Campus Initiatives Financial Literacy Degree-Applicable Credit rules
Growing summer online offerings
Creating winter intercession term

7. Results
Super-senior counts are at historic lows

8. Results
Super-senior counts are at historic lows

9. Confessions – Part 2 This was all done after a crisis:
Overestimation of continuing students
caused 5% budget cuts

10. Early predictions
Given the enrollment in Fall, predict enrollment at Fall +1
With nothing more than historic return rates available

11. Historic return rates

12. Assume: Anything can happen
5 class levels of students
10 years of data
Any combination is possible
161,051 possible combinations

13. Assume: Anything can happen

14. Checkpoints and Predictors
New
New
Continuing
Fall
Enrolled
Students
Continuing
Spring
Enrolled
Students
Fall
Enrolled
Students
Spring Grads
WDT
Fall Grads
WDT

15. Predictor – Student Registration

16. Key Conversation - Registrar
Sharing of data and progress
Understanding of how students register
Time ticketing
Variable dates for opening of registration

17. Changing Perspective

18. Key Conversation - Admissions
Completely different starting point
Understanding of their key indicators:
Admissions populations
Active deposits / deadlines
Instant yield

19. Fall Freshmen

20. Fall Transfers

21. Calculating values 20 days after registration opens:
91.7 to 95.4 complete
If 3,890 are registered, predict:
4,060 to 4,242 continuing
4,132 (mean) most likely

22. Presentation Red line: original target Teal: min to max potential
Needle: current projection

23. Dashboard

24. Lessons Learned Engage with partners early
Use student behavior as key predictive element
Align dates for greater accuracy
Use dashboards for delivery

25. Pay attention, keep in contact
Change in business practice will invalidate projections
Watch early warning indicators

26. Futures Student success analytics integration Student device tracking
Access card swipe tracking

27. Questions?