1. LEVERAGING TECHNOLOGY FOR STREAMLINED RESIDENCY
Elena Herron Chappelle & Heather Peterson
RMACRAO | July 18, 2019

2. ROAD MAP Identification of the Problem & Critical Questions
Intentional Technology Integration
Designing an Initial Residency Verification Form
Defining an Algorithm & Integration

3. Old Process Map

4. ASKING CRITICAL QUESTIONS
How do we make residency more student-centered?
How does this touch the business processes of other departments?
Can we create a basic scoring system to make easy decisions?
How can we leverage data validation to encourage accurate responses?
What pieces of data can be automatically fed from the form into the student record?
How can we make sure this images to student record without manual work?
Does legal counsel approve?
Did you get the project on the Information Technology department list?

5. Creating a New Tuition Classification Process
MAPPING EXISTING Process
engaging stakeholder feedback
Designing an ideal FORM & workflow
Our form does not exist in a vaccuum. There has to be a solid workflow in place both technologically and otherwise.

6. Creating a New Tuition Classification Process
MAPPING EXISTING Process
engaging stakeholder feedback
Designing an ideal workflow

7. CORE CONCEPT MAP Algorithm Automation System Integration
IF/THEN Logic
System Integration
Data Validation

8. Designing AN Initial Residency Verification Form
At CU Anschutz Tuition Classification is all completed by the Office of the Registrar
100% of students are required to complete an Initial Verification of Residency Form
The new electronic form is accessible only to students who are provided with link
OnBase Form allows for custom action logic

9. STEP 1: IDENTIFYING THE STUDENT

10. STEP 1: IDENTIFYING THE STUDENT
Elements Needed for Search Match
Full Name
Address
Age (DOB)
Elements Needed for Data Integration
Academic Program
Intended Start Term
Elements Needed for Residency Verification
Citizenship
Age (DOB)
Marital Status
Intended Start Term
Elements Needed for Communication
Address

11. FIRST PIECE OF COMPLEX LOGIC
DETERMINING EMANCIPATION
Use program drop down menu response to identify term start date
Term start date can be used to calculate age on first day of class
IF student is 22 or younger THEN page 2 of the form will require parent information

12. FIRST PIECE OF COMPLEX LOGIC
DETERMINING EMANCIPATION
Use program drop down menu response to identify term start date
Term start date can be used to calculate age on first day of class
IF student is 22 or younger THEN page 2 of the form will require parent information

13. STEP 2: SIMPLE IF/THEN LOGIC
IF student does not claim to be a Colorado Resident THEN the form moves directly to disclosure, signature, and close.
IF student claims Colorado Resident status THEN the form will continue to further pages with verification questions.
This is the simplest logic available. CU Denver was already leveraging this capability with Slate. Many schools with online forms for residency are probably at least doing this much. If a student tells us they are NOT a resident then all we need to do is display a disclosure and collect a signature. No other actions should really be required. In our form it simply determines where students move after the first page.

14. Other IF/THEN Screening Questions
In version 2.0 of our form we are going to bring this military status question to the first page. That way we can capture more students up front who may be eligible for resident tuition rates.

15. Other IF/THEN Screening Questions
Military Status
WICHE Eligible Students
Citizenship
In version 2.0 of our form we are going to bring this military status question to the first page. That way we can capture more students up front who may be eligible for resident tuition rates.

16. FIELDS WITH DATA VERIFICATION
Address/State/Zip Code
Social Security Number
Colorado Driver’s License Number
Colorado License Plate Number
All Date Fields

17. Disclosure and Electronic Signatures

18. Defining the Algorithm
The algorithm scores a student based on responses
ONLY students claiming residency have the algorithm applied
The algorithm can be overwritten by any of the auto-Under Review responses (these students are NOT coded with a residency and a flagged for further review)
Most of us use algorithms everyday. If you type anything into a search engine you are utilizing an algorithm, albeit one that is much more complex than the one we are going to talk about specifically in terms of this form. Our algorithm for residency was developed and tested by us

19. Automatically flagged for Review
Any YES answer to a military active duty or veteran question
Mailing or permanent address outside of CO
Taxes paid in another state within the past year
Absence of 12 months or more from the state
Under 23 and married
Noncitizens who indicate an eligible visa type

20. Automatically flagged for Review

21. Scoring the Algorithm Highest Scoring Elements:
Dates of Residency – 1 year or more continuously prior to start date
Individual Income Taxes filed in CO in most recent year
CO real residential property ownership
Mid-Scoring Elements
CO driver’s license
CO vehicle registration
CO voter registration
CO high school graduation

22. Scoring the Algorithm Negative Scoring Elements
Less than 1 year of continuous physical presence in CO
Failure to file CO individual income tax IF taxes filed in another state
Non-Scoring Elements
CO employment
Maintenance of home outside of CO

23. Score Category Action -2 to 2 Nonresident
Coded as Nonresident in Peoplesoft, student receives automatic communication with petition instructions and link.
3 to 6
Under Review
Coded as Under Review in Peoplesoft, student receives notification that a decision will be forthcoming or more information may be needed, form appears in workflow queue for TCO to review.
7 +
Resident
Coded as Resident in Peoplesoft, student receives automatic communication.

24. Items to run by Your IT Crowd
When/How often can resources be allocated for development and future maintenance?
Behind portal/SSO or link
Integration of Data (can these systems talk the way you want)
Load Balancing on Server
Managing a Go Live
Version 2.0

25. WARNING: ONE SIZE DOES NOT FIT ALL
Our algorithm was tested on randomized populations from each of the 10 admissions pools.
Office of the Registrar engaged in months of testing on each population.
This testing helped us fine-tune an algorithmic score for graduate/professional medical population.
Things I might do differently for a largely undergraduate population: I would give much more weight to Colorado High School graduation certainly.

26. Thank You! ELENA HERRON CHAPPELLE TUITION CLASSIFICATION COORDINATOR
(303)
Heather Peterson CU ANSCHUTZ campus registrar
(303)