1. Improving Graduation Rates Using Data Insights and Predictive Modeling
Jon
EDUCAUSE September 30, 2014

2. Predicting Success Increasing Student Success
Incorporating Proactive Student Support
Taking a High Touch High Tech Approach
Tracking Institutional Effectiveness
Defining the Technological Solution
Jon
Predicting Success

3. From Data Reports to Analytics
Jon
From Data Reports to Analytics

4. Really Knowing Our Students
Goes Beyond Reporting
Pattern recognition
Predictive
Prescriptive
Inferential
Jon
Really Knowing Our Students

5. Jon

6. Sheila
Encompasses 23 communities in the northwest suburbs of Chicago; 200 square miles and a population of 555,100 citizens.
Approximately 30,000 businesses are located in the District.
The College’s annual FTE credit enrollment stands at approximately 22,000 students.
Total headcount exceeds 40,000 and includes individuals of all ages attending credit, continuing education, customized, and extension courses at the Harper campus or at other district locations.

7. Increasing Graduation Rates
Graduation Rate increased from 14% to 24% in 5 years
New Reactive Programs
Early Alert
Supplemental Instruction
Completion Concierge
Summer Bridge for High School Students
All data based, reactive solutions
New, Proactive Systemic Solutions
Sheila
Increasing Graduation Rates

8. Improving Student Success Support Across the Pathway
Sheila
Improving Student Success Support Across the Pathway

9. Aggregating Data What if we combined all that we know: High School GPA
Placement Scores
Attendance Patterns
Engagement on Campus
Progress in Course Work
Age
Pell Eligible
Full Time vs. Part Time
Ethnic Background
First Generation College
Attendee
Sheila
Aggregating Data

10. Removing the Guesswork
Abilities
Counseling
Program of Study
Course Scheduling
Support Services
Placing into success interventions prior to experiencing failure
YES NO
MAY BE
Sheila
Removing the Guesswork

11. The Student Retention Model
Ethnic Group
First Generation
Gender
FT/PT Status
High School GPA
ACT/SAT Score
Current GPA
PELL Grant
Campus Activities
Student Data
Course Data
College Data
Model
Variable
Advisor
Student
Student Retention Predictive Analytics Model
Reports & Alerts
Reports & Alerts
Sheila
Early Intervention
Risk Factor

12. Institutional Operational Student
Dashboards
Sheila
Institutional
Operational Student

13. Sheila
The data has been modified and is not valid

14. Sheila

15. Sheila

16. Sheila

17. Patrick

18. Patrick

19. Patrick

20. Student Information
Patrick

21. Advisor Use Case: Personalized Data-Driven Intervention
Select Cohort
Select Student Cohort
Average Risk score by Cohort year
Average Grade by Cohort year
At-Risk Student List
Patrick
Identify students with high risks
Standardized Scores and
Quick Access
Customizable to meet specific
Harper definitions of At-Risk

22. Advisor Use Case: Personalized Data-Driven Intervention
Student Profile
Understand the situation
What has contributed to the scores
Student background
Academic performance
Interactive Levers
Patrick
Simulate what-if scenarios
“Tweak” actionable variables
See predicted results

23. Career Selection Personalization Course Planning Integrated Support
Predictive Analytics
Improves
Jon - optional
Integrated
Support
Completion
Persistence

24. Student Analytics = Proactive Personalized Student Success
Jon
Student Analytics = Proactive Personalized Student Success

25. HARPER COLLEGE
Jon
Questions