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June 2017

Institutional Data Users Group. Numbers & Narratives: Using Institutional Data to Create Actionable Outcomes for Enrollment Management & Student Success. June 2017. June 14 th 2017. Institutional Data Users Group. Session Overview. Overview of Enrollment Management Data Utilizations

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June 2017

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  1. Institutional Data Users Group Numbers & Narratives: Using Institutional Data to Create Actionable Outcomes for Enrollment Management & Student Success June 2017 June 14th 2017

  2. Institutional Data Users Group Session Overview • Overview of Enrollment Management Data Utilizations • Overview of Student Success Data Utilizations • Planned initiatives for utilization of data to influence outcomes in Enrollment Management & Student Success Michael Hovland Director of Enrollment Management Data Analytics Danielle Martinez Assistant Director of Academic Support & Retention Kirk Kluver Director of Admissions

  3. The College Admission Landscape Institutional Data Users Group • Changing demographics • Reliance on tuition revenue • Increased competition • Changing value proposition • Student’s approach to college search

  4. The Data Imperative Institutional Data Users Group • Admissions professionals have historically relied on gut feelings, anecdotes, and year-end reviews rather than data to determine strategy and priorities • In the new admissions landscape, we need data to make real-time decisions throughout the admissions cycle • Our resources are limited; we use data to leverage the time and money we have

  5. Applications of Predictive Modeling and Other Data in Diverse Areas Institutional Data Users Group • Prospect Development (recruiting graduates-to-be) • Marketing and communications • Recruitment • Scholarships and Financial Aid • Presidential scholarships • Financial Literacy • Admissions waiting lists • Orientation • Course and section planning

  6. Institutional Data Users Group Use of Data in Prospect Development • The admissions funnel moves from pre-prospects to prospects to admits to enrolls • The higher you are on the funnel, the more expensive it is to communicate with prospective students • We are using geo-demographic data (neighborhood clusters and high school clusters from College Board) to focus search purchases

  7. Use of Data in Prospect Development Institutional Data Users Group

  8. Use of Predictive Modeling Datain Marketing and Communications Institutional Data Users Group • Use predictive models for admits and prospect to determine which prospective students will receive print publications • Start with a target numeric goal • Omit and protect certain groups of students based on characteristics and UI shaping goals • Use predictive modeling scores to fill in the gap between the number of protected students and the target numeric goal

  9. Use of Predictive Modeling Data in Recruitment Institutional Data Users Group • Territory management • Planning off-campus outreach initiatives such as visits to high schools and college fairs • Identify in-cycle trends with Tableau dashboards • Postcard writing projects by admissions counselors and academic departments • Combine probability with shaping goals to determine students to contact • Modified Telehawk tool to use predictive modeling and shaping goals

  10. Real-Time Data with Territory Management & Counselor Dashboards Institutional Data Users Group

  11. Real-Time Data with Territory Management & Counselor Dashboards Institutional Data Users Group • Many of our on-campus and off-campus events fill to capacity and not always with the students we are most interested in • Looking at ways to use data to move toward more invitation-based recruitment events

  12. Use of Predictive Modeling Datain Financial Aid Scholarships Institutional Data Users Group • The overall yield rate for incoming freshmen is under 30% • This means that UI does not spend 70 cents of every dollar of scholarship moneys offered • To project total scholarship costs, staff multiply the cost of every scholarship offered times the probability of enrollment for each student • FA staff also use projected scholarship headcounts to do 6-year cost projections

  13. Use of Predictive Modeling Data with Presidential Scholarships Institutional Data Users Group • Every year the UI awards 20 Presidential Scholarships to incoming freshman • Several hundred scholarship applications are pared down to a group of 30-40 finalists • Probabilities are used to determine how many finalists are to be offered presidential scholarships

  14. Financial Aid Literacy Project Institutional Data Users Group • This spring used financial aid data to identify more than 500 admitted students for Fall 2017 for whom the UI did not look like a good financial fit • Many of these students had large student loans that would be difficult to repay if students were not academically successful at the UI • UI reached out and invited these students to meet with a UI Financial Literacy Counselor

  15. Use of Predictive Modeling Data with Admissions Waiting Lists Institutional Data Users Group • Last year the UI Admissions Office instituted a waiting list for students applying after May 1 • This year the waiting list was instituted on March 1 • Probabilities are used, along with student profile data, to determine how many students to admit from the waiting list

  16. Use of Predictive Modeling Data in Orientation Institutional Data Users Group • Incoming freshmen attend one of series of on-campus orientation programs throughout the summer • Students are scheduled (and advisors assigned) based on program of study • Orientation staff use probabilities to determine the likely number of slots needed for each major

  17. Institutional Data Users Group Sample of Weekly Orientation Planning Data Report

  18. Use of Predictive Modeling Data in Course and Section Scheduling Institutional Data Users Group • Academic departments can use probabilities to determine the number of adjunct instructors to hire and the number of sections of courses to offer

  19. Establishing Multiple Types of Enrollment Predictors Institutional Data Users Group • Predictive modeling scores • Longitudinal trends for applications, admits, and admissions acceptances • Housing applications • Admissions deposits • Orientation reservations • FAFSAs received • ACT and SAT scores received

  20. Predictive Modeling Enhancements Institutional Data Users Group • Predicted first-year GPA for entering freshmen • Retention predictions • First year to second year • Second year to third year • Third year to fourth year • Graduation predictions • Four-year and six-year graduation likelihood

  21. Challenges of Retention Models and How They Differ from Recruit Models Institutional Data Users Group • Student academic profile and course-taking behaviors don’t change frequently in high school • At UI we have a great deal more data that changes frequently: • Changes in program of study and college • Mid-term, term, and cumulative grades • Course drops and adds

  22. Applications of Predictive Modeling and Other Data in Student Success Institutional Data Users Group • Financial Literacy • Parent & Family Outreach • Mental Health • Populations Specific Support • Early Intervention • Transition Programs • Alcohol Harm Reduction • Academic Support

  23. Student Success at Iowa Institutional Data Users Group University of Iowa students succeed when they achieve personal and institutional educational goals. Successful students develop skills and knowledge, become more mature in their thinking, assume greater responsibility for their own lives and learning, develop understanding of diversity and multiculturalism, and become effective leaders. Student success at The University of Iowa is a shared enterprise. Students succeed by active engagement in educationally purposeful activities. Faculty, staff, and students create formal and informal learning opportunities on campus and off, and policies, programs, and practices that foster student engagement. The University measures students and institutional success in undergraduate education by examining a variety of indicators, including measures of learning, persistence, graduation, engagement, health and well being, and opportunities after graduation. From Definition of Student Success, Student Success Team

  24. Academic Support & Retention Institutional Data Users Group Academic Support & Retention coordinates campus-wide programs and initiatives that facilitate the academic success of all undergraduate students.

  25. Framing Student Success & Retention Institutional Data Users Group • Profile: Who are our students and how do they change as they experience the university? • Progress: Are students able to make progress towards their degree and other personal measures of success? • Process: Are there institutional barriers to students succeeding? • Promise: Are we meeting the expectations that we set or sell when recruiting and transitioning students to the university?

  26. Data Driven Early Intervention Efforts Institutional Data Users Group • A student success platform used by faculty, staff, and administrators to support first-year and new transfer students’ transition to the University of Iowa. • Cohorts • 1st time, 1st year students • New Transfer Students • All grade levels of TRiO Student Support Services • Course Associated

  27. The Process Institutional Data Users Group 1st Year Students On Iowa! (Fall Semester) Be Better (Spring Semester) Pre College Preparation (Fall Semester) Transfer Students Transfer Experience TRiO SSS Students TRiO SSS Services and Experience All Students Belonging & Fit Homesickness Finances Academic Behaviors Grit & Resiliency Involvement Commitment Time Spent & Management On/Off Campus Living Safety & Mental Health Open-Ended Overall Experience

  28. Creating an Actionable Network of Support Institutional Data Users Group Student Connections – Housing Connections to Residence Education Staff for students who live on campus. Off campus students are assigned groups of staff across campus to strengthen connections. Student Connections – Academic Connections to Undergraduate Colleges Staff & Faculty and the Academic Advising Center Coordinated by Academic Support & Retention Powered by Information Technology Services Other Campus Resources & Referrals Over 20 campus resources that serve students and can follow up with student concerns and be a referral source (e.g. University Counseling Service, Center for Student Involvement and Leadership, Financial Aid). Student Connections - Campus Life Connections to offices that serve subpopulations of students (e.gInternational Student and Scholar Services, Center for Diversity & Enrichment, Athletics)

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  34. Student Transition Narrative Institutional Data Users Group Top 5 Areas Most Correlated to Student Retention Level of Homesickness Level of Commitment to Institution Level of Social Integration Level of Satisfaction with the Institution Financial Mean Top 5 Areas Most Correlated to Fall Term GPA Basic Academic Behaviors Academic Integration Time Management Skills Academic Self-Efficacy Advanced Academic Behaviors

  35. Impact of Data on Student Transition Programs Institutional Data Users Group • Added sessions regarding academic expectations and growth mindset messaging • Additional parent & family sessions • Transfer program redesign • Added sessions on succeeding in math, time management, and writing skills • Event redesign to better integrate students to campus traditions • Off-campus student programming

  36. Impact of Data on Financial Literacy Institutional Data Users Group • Reviewed over 250 students who rated finances as top concern. Each student was reviewed and contacted with individualized steps for future success and financial stability. • Outreach to students who expressed an interest in learning more about budgeting money and/or their loan obligations. • Outreach to students who expressed interest in working and/or received work-study but didn't understand the process. “Excelling@Iowa gives the Student Financial Aid office an opportunity to help students deal more proactively with finances before it becomes a crisis. It gives the student a comfortable way to reach out for help. When we email or call the students based on their survey results or open-ended responses, they are generally very relieved and grateful that someone is there to help them.”

  37. Impact of Data on Academic Success Institutional Data Users Group • Expansion of Course Based Interventions • Supplemental Instruction • Peer Led Undergraduate Study • Use of Student Reports to guide assignments *Peer group considered all students in the fall 2016 enrolled in both CHEM:1070 and MATH:1005 within the same ACT and high school GPA range

  38. Impact of Data on Parent & Family Webinar Institutional Data Users Group • Created monthly Parent & Family Webinars to better target parents & families • Expanded messaging for Parents & Families during orientation and new student transitions • Send letters to parents & families of new students

  39. Impact of Data on Harm Reduction Institutional Data Users Group Added a goal to institutional harm reduction plan about supporting students who do not drink, based on responses to “What I Like Most/Like Least” question.

  40. Impact of Data on Mental Health Outreach Institutional Data Users Group • Analysis determined that mental and emotional health is the top reason to why students were actively withdrawing and added in intervention plan to support students • Expansion of student care initiatives • Dean on Call program

  41. Impact of Data on Specific Populations Institutional Data Users Group • Being Black at Iowa • International Student Support • First Generation Focus • Transfer Students

  42. What’s Ahead for Enrollment Management? Institutional Data Users Group • Use of Predicting Modeling Data in Housing • Enrollment probabilities can be summed to project: • Likely occupancy for each residence hall • Likely size of each living/learning community • International Students • Supplement Enrollment Mgmt BI Dashboards to support 5 year Enrollment Mgmt plan at Collegiate and Institutional levels • Financial Aid BI Dashboard and Data Analysis to support institutional Net Revenue objectives

  43. What’s Ahead for Student Success? Institutional Data Users Group • Student Withdrawal Process • Expansion of Excelling@Iowa to all students • Academic Support Tracking • Expansion of faculty integration • Incorporation of High Impact Practices into the Retention & Pipeline Models • Individual Student Influencing Attributes • Partnership with BISSC on Student Success BI Dashboards and data mining/machine learning to identify areas of opportunity for improvement in outreach, Institutional processes or relationship management.

  44. Institutional Data Users Group For IDUG Executive Committee and Session Feedback or Ideas IDUG-FEEDBACK@IOWA.UIOWA.EDU For IDUG Peer to Peer Discussion, Collaboration and Sharing IDUG-DISCUSSION@LIST.UIOWA.EDU IDUG Website http://itcommunities.uiowa.edu/content/institutional-data-users-group Follow us on Twitter @UIowaIDUG

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