Moving from Enrollment-based Funding to Performance-based
As of July 2015, 32 states have moved to a model that focuses state higher education funding on performance, not enrollments. Where universities and colleges once received funding based on the number of full-time enrollments on a given class day, the transition to performance-based models allocates a significant portion of funding on performance indicators that may include but are not limited to: time to degree, course completion, transfer rates, number of credit hours completed, or number of degrees awarded. In order to avoid colleges and universities only admitting those students deemed (correctly or incorrectly) most likely to succeed, performance indicators can also include points and weights for underserved populations including low-income and minority students. Performance-based funding was envisioned to align more closely with state goals, priorities and strategies.
The current Ohio performance funding model is structured to allocate subsidy as follows: 50 percent on course completions, 25 percent on completion milestones, and 25 percent on success points. Additional weights are applied to students who are Pell eligible, 25 years of age or older at start, and/or African American, Hispanic or Native American.
This funding model has heightened Ohio institutions’ focus on student challenges and completion barriers and as a result, much work is underway across the state to strengthen student success. Sinclair College, a large, urban two-year college in Dayton, Ohio is leveraging analytics as part of their approach.
Serving Diverse Student Populations
For Sinclair, the challenge is real. “Some of our students arrive facing some seemingly insurmountable challenges,” said Laura Mercer, chief of staff at Sinclair College.
“Nationally, nearly 60 percent of students are not adequately prepared for college work,” said Mercer. “Approximately 30 percent are first generation. If no one around you has succeeded in college, who mentors you and helps shape your expectations? How do you know how much and time and effort you need to commit to your studies to be successful?”
Additionally, many students are balancing complex lives — 24 percent of higher education students qualify as both first-generation in college and low income. Many work (sometimes multiple jobs), are raising families, and may have tenuous financial scenarios according to Mercer.
Competition for Diminishing Resources
The National Student Clearinghouse recently released a report suggesting that only 39 percent of first-time community college students earn a credential within six years. We need to do better to help more students succeed in a more expedient manner. It’s the right thing to do, and it will have a positive effect on institutions’ sustainability especially in light of performance-based funding scenarios.
So what is Sinclair doing in order to meet this challenge?
“Ohio has transitioned to a funding formula that is 100 percent performance based on performance outcome measures,” she said. “There’s a limited pool of resources that will only grow as institutions demonstrate success in this new outcome-based funding environment.”
“Institutions that move the needle the furthest, the fastest, stand to see the most substantial returns. One of the strategies we’ve embraced at Sinclair is to invest in analytics because it’s a tactical approach that we believe will allow us to best help our students succeed and will result in an improved bottom line and an increased return on investment (ROI).”
Ohio Performance-Based Funding Model
For FY2015, two-year colleges are funded as follows:
50% Course Completions
25% Completion Milestones
25% Success Points
Completion Milestones defined as:
Certificates over 30 credit hours approved by the Board of Regents
Students transferring to any four-year institution with at least 12 credit hours earned at that community college, state community college, or technical college
Success Points defined as:
Students earning their first 15 credit hours
Students earning their first 30 credit hours
Students earning at least one associate degree
Students completing their first developmental course
Students completing any developmental English in the previous year and attempting any college level English either in the remainder of the previous year on any term this year
Students completing any developmental Math in the previous year and attempting any college level Math either in the remainder of the previous year on any term this year
Students enrolling for the first time at a University System of Ohio main campus or branch this year and have previously earned at least 15 college level credits at this community college
Additional weights are applied to students who are Pell Grant eligible, Native American, African American, or Hispanic, or are 25 years of age or older when they first enroll at a state institution of higher education.
Four-year colleges are funded as follows:
50% Degree completion
30% Course completion
20% Doctoral and Medical Set Aside
Additional weights are awarded for degree completion in STEM fields. Course and degree completions are calculated on a three-year average.
Sinclair sees this work as a strategic investment and expects a requisite payoff, anticipating that incremental changes will bring about substantial educational and financial returns. Mercer lists annualized ROI examples that show how incremental changes can bring about substantial returns at Sinclair College:
Each 1 percent improvement in course and credential completions over and above average sector improvements brings an additional $425,000 in state funding.
Each 1 percent improvement in student retention results in $200,000 in additional net income.
Each 1 student improvement in college-wide average class size brings about $1.7 million in cost savings.
Sinclair has a long history in data analytics. They’ve had a data warehouse and SAS for more than ten years and have federated nearly a terabyte of information. Sinclair is focusing on two key themes to use these data to help students succeed: (1) equipping faculty and advisors with better, deeper data, and (2) equipping students with better decision support.
Equipping Faculty and Advisors with Deep Data
“We know student performance in courses is one of the most critical, granular aspects of their success,” said Mercer. “By better understanding the behavior exhibited by past students (both successful and non-successful) in each course we can help faculty better understand the trajectory of their current students’ behavior. We are using analytics to help our faculty more easily discern what is most important to monitor and focus on for each student’s success.”
“It’s also critical we give advisors and coaches better information and tools,” said Mercer who points to case loads of 300-400 students per advisor. “When advisors meet with students, they typically only know the student’s demographic and past performance. We can do better.” Mercer advocates for providing advisors with effective means to triage large caseloads and to more effectively and easily identify potential problems and opportunities within them. “The conversation will change when an advisor has access to students’ real-time performance data in each class—not just grades—but also engagement, attendance and more.”
Enabling Better Student Decision Support
Mercer says it’s important to not only outfit faculty and advisors with insights from data, but to also get this information into the hands of students so they can make better decisions.
“The first aspect of this involves performance coaching,” she says. “We need to identify, beyond grades, the kinds of student behaviors that lead to success. These might include things like time spent on course materials, participation in events, and utilization of services. We need to then to provide this information to students in an engaging and intuitive way that will show them where they stand in comparison to their peers and typically successful students, and then to nudge or coach them to improve.”
“The second aspect of providing students with better decision support relates to equipping them to make better informed choices at both a granular level (like choosing courses), and programmatically (like selecting programs of study) so they can better understand the implications of potential decisions and actions, such as the time and costs to completion.
We anticipate that the end result of our work to leverage analytics to improve student success will be better student outcomes as well as a sound return on our investment. “Students come to us seeking education as a vehicle to better lives,” said Mercer. “We want to do everything we can to help them succeed.”
Laura Mercer is currently Chief of Staff at Sinclair. At the time this was published she served as the Director of Research, Analytics, and Reporting. She has 27 years of experience in comprehensive planning, implementation and management within the higher education environment. She maintains responsibility for the institution’s data warehouse and analytics infrastructure, decision support, state and federal reporting, and institutional research. Ms. Mercer provides leadership and project management for Sinclair’s comprehensive predictive analytics and student success tools initiative, LIFT!