Performance-Based Funding

Today’s economic environment has forced states to carefully contemplate how to allocate funds to different public services, such as transportation, health care, and education (Miao, 2012). Consequently, state governments have continued to allocate less money each year to public higher education institutions due to the economic environment and the perception that institutions do not carefully allocate resources to help support students (Mitchell et al., 2019). Public institutions have responded to these yearly funding cuts by increasing tuition rates, limiting the offering of courses available to students, cutting faculty and staff members, and in worst-case scenarios, closing campuses (Mitchell et al., 2019). Previously, states have commonly allocated funds to public institutions based on enrollment numbers; a process that “reinforces their commitment to college accessibility and ensures a relatively equitable distribution of per-student spending across institutions” (Miao, 2012, p. 1). However, large enrollment numbers do not necessarily signify that a higher education institution is performing well (Miao, 2012). As a result, some leaders in higher education have turned to performance-based funding models that not only focus on enrollment numbers but also college retention and completion rates.

According to Miao (2012), performance-based funding is “a system based on allocating a portion of a state’s higher education budget according to specific performance measures such as course completion, credit attainment, and degree completion, instead of allocating funds based entirely on enrollment” (p. 1). Performance-based funding differs from state to state, as each state uses its own combination of indicators and outcomes listed in the above definition to divide funding among its institutions (Obergfell, 2018). Additionally, some leaders in higher education say that performance-based funding also focuses particularly on Pell-Grant and minoritized students (Obergfell, 2018). These individuals often find themselves completely left out of in enrollment-based funding models (Obergfell, 2018). Proponents of performance-based funding believe that this model helps support disadvantaged and minoritized students because it forces public institutions to show how they have used their funds to help all students throughout their college careers (Miao, 2012). As a result, performance-based funding incentivizes higher education institutions to continue working towards improving these key performance metrics for entire student body populations, not just specific groups of students (McKinney & Hagedorn, 2016).

During 1979-2007, 26 states attempted to use performance-based funding as a method to allocate funds to public higher education institutions (Miao, 2012). In 1979, Tennessee became the first state to utilize a performance-based funding program (McLendon & Hearn, 2013). The state’s goal in switching from primarily enrollment-based funding to performance-based funding was to address widespread dissatisfaction with Tennessee’s current method of allocating funds to public higher education institutions (McLendon & Hearn, 2013). Additionally, higher education leaders within the state of Tennessee believed that this change would also help lower the growing concern among individuals in the general public (McLendon & Hearn, 2013). The Tennessee program had multiple features that made it attractive to other states, such as focusing on performance metrics that varied in scope but limited in number, stressing routine reviews of the institution, and concentrating on continual internal improvement within all institutions (MeLendon & Hearn, 2013).

Although the spread of performance-based funding was primarily contained in southern and midwestern states throughout the late 20th century, by 2000, performance-based funding had spread throughout the entire country (Miao, 2012). During this period, however, 14 states that had created performance-based funding models discontinued these models for various reasons (Miao, 2012). Administrators cited that the models were inflexible to institutional differences, that they failed to allocate enough money to create realistic incentives for colleges to improve, and that they focused too much on graduation rates instead of gradual progress made throughout an individual’s college career, such as course completion (Miao, 2012). Despite many states scrapping their original performance-based funding models, declaring them as ineffective, performance-based funding has once again gained traction in today’s higher education environment. As of January 2020, at least 30 states use some sort of performance-based funding program to allocate funds (Gandara, 2020).

Indiana uses a performance-based funding model that focuses on completion, progression, and productivity metrics (Callahan et al., 2017). Four of these metrics apply to all public higher education institutions: Degree completion, at-risk student degree completion, on-time graduation, and a parameter defined by the institution (Callahan et al., 2017). For example, institutions can receive an additional $23,000 for each bachelor’s degree completed on-time (Callahan et al., 2017). Three of these performance-based metrics apply specifically to the different missions of community colleges and universities: High-impact degree completion, student persistence, and remediation success (Callahan et al., 2017). For example, institutions can receive an additional $20,000 for each high-impact bachelor’s degree conferred (Callahan et al., 2017). These funds are in addition to the $8,000 an institution already receives for each bachelor’s degree conferred (Callahan et al., 2017). In 2017, Indiana awarded 6.5 percent of its funds to higher education institutions based on this performance-based model, a modest percentage in comparison to many other states (Callahan et al., 2017).

Tennessee’s current performance-based funding model, developed in response to the Complete College Tennessee Act of 2010, eliminates enrollment numbers from its funding model (Tennessee Higher Education Commission [THEC], n.d.). Instead, two sets of performance-based funding models, one for four-year institutions and one for two-year community colleges, exist to help reflect the priorities and mission of each institution (THEC, n.d.). Performance-based outcomes in these models generally consist of students accumulating a certain amount of credit hours, student completion using the number of degrees awarded, the number of degrees awarded per 100 full-time equivalent students, and six-year graduation rates (THEC, n.d.). As a result, outcome data, such as six-year graduation rates, are weighted to indicate the importance of that outcome at a particular institution (THEC, n.d.). For example, Austin Peay State University (APSU) receives 10.0 percent of its funding based on its six-year graduation rate (THEC, n.d.). In comparison, the University of Memphis receives 17.5 percent of its funding based on its six-year graduation rate, reflecting that six-year graduation rates are more critical to the mission at the University of Memphis that at APSU (THEC, n.d.).

When looking at research, evidence exists that demonstrates that well designed performance-based funding models can provide numerous benefits to higher education institutions. First, research shows that performance-based funding encourages more reliable data collection and tracking efforts within institutions (Li, 2019). These tracking and collection efforts allow institutions to make intentional changes to academic curriculum and policies (Li, 2019). As a result, institutions have improved retention rates and reduced the number of excess credit hours earned by students to graduate (Li, 2019). Second, two-year colleges in Washington, Tennessee, Ohio, and Florida have made significant improvements in its developmental education courses due to performance-based funding (Dougherty et al., 2016). With more students passing developmental education courses in math, reading, and writing, the retention rates at institutions in these states have significantly increased (Dougherty et al., 2016). Last, research shows that performance-based funding sparks changes that ultimately lead to institutions adding additional resources for students (Li, 2019). These resources include the development of first-year orientation programs, adding support to tutoring services, and increasing connections to employers to help students find quality internship and job opportunities (Li, 2019).

Despite the benefits that this research suggests, performance-based funding also has its challenges. First, evidence shows that performance-based funding leads to two-year institutions issuing more educational certificates than associate degrees (Li, 2019). Although certificate programs do provide economic benefits in some sectors, such as business or nursing, they often offer fewer benefits in comparison to associate degrees (Li, 2019). As a result, most individuals who receive certificates do not experience an increase in pay or the likelihood of finding a job (Li, 2019). Next, due to performance-based funding, four-year institutions are becoming more selective when admitting students (Umbricht, Fernandez & Ortagus, 2017). Since performance-based funding models focus on meeting specific retention, progression, and graduation outcomes, institutions can increase the likelihood of achieving these outcomes by only admitting students with high GPAs and standardized test scores (Umbricht et al., 2017). When institutions restrict access to less-academically prepared individuals, they restrict admission to college for many students from disadvantaged backgrounds who performance-based funding needs to support (Umbricht et al., 2017). Last, an unintended consequence of performance-based funding is that academic standards are often lowered (Dougherty et al., 2016). Since students must make progress and ultimately graduate for institutions to receive performance-based funds, faculty at some institutions have reported instances of passing students who should have failed a class to reach performance-based goals (Dougherty et al., 2016).

If I were working for a state legislature that was deciding on whether to use a performance-based funding model, I would recommend that the state makes a small percentage of funding for public higher education institutions based on a performance-funding model. When deciding how to create quality metrics for a performance-based funding model, it is crucial to observe the best practices found in research. First, criteria for performance-based funding should promote alignment between state priorities and the mission, vision, and goals of specific institutions (Miller, 2016). Additionally, quality metrics must be straightforward and understandable for all stakeholders (Miller, 2016). Direct and understandable performance-based funding metrics allow institutions to improve their performance over a significant period of time and enable individuals to be held accountable for their actions (Miller, 2016). Last, performance-based metrics should be “difficult to game” (Miller, 2016, p. 5). Creating performance-based incentives on a particular set of metrics may produce responses by institutions that want to artificially increase their performance on those metrics, such as passing students who should have failed a class to meet retention and graduation performance-based metrics (Miller, 2016).

If leaders in higher education meticulously create performance-based funding outcomes that follow best practices, it can significantly improve academic curriculum and policies, reduce the number of excess credit hours earned by students to graduate, and support disadvantaged students. However, if higher education leaders do not learn from the mistakes made by previous performance-based funding models, there are significant negative consequences. Without quality metrics in place, performance-based funding can reduce the number of associate and bachelor's degrees earned in community colleges, restrict access to less academically prepared students, and lower academic standards to meet specific performance-based funding metrics. By actively involving key stakeholders in the model’s design, gradually phasing in new measures, and frequently evaluating the success of the model, performance-based funding has the opportunity to achieve success in many states throughout the country (Miao, 2012).

---

References

Callahan, K., Meehan, K., Shaw, K. M., Slaughter, A., Kim, D. Y., Hunter, V. R., & Lin, J. (2017). Implementation and impact of outcomes-based funding in Tennessee. Philadelphia, PA: Research for Action.

Dougherty, K. J., Jones, S. M., Lahr, H., Natow, R. S., Pheatt, L., & Reddy, V. (2016). Performance Funding for Higher Education. Baltimore, MD: John Hopkins University Press.

Gandra, D. (2020). Performance-based funding for universities is gaining in popularity, here’s why it’s a bad idea. Retrieved from https://www.marketwatch.com/story/performance-based-funding-for-universities-is-gaining-in-popularity-heres-why-its-a-bad-idea-2020-01-09

Li, A. Y. (2019). Lessons learned: A case study of performance funding in higher education. Washington DC: Third Way.

McKinney, L., & Hagedorn, L. S. (2016). Performance-based funding for community colleges: Are colleges disadvantaged by serving the most disadvantaged students. The Journal of Higher Education, 88(2), 159-182.

McLendon, M .K., and Hearn, J. C. (2013). The resurgent interest in performance-based funding for higher education. The American Association of University Professors, 99(6), 25-30.

Miao, K. (2012). Performance-based funding of higher education: A detailed look at best practices in 6 states. Washington DC: Center for American Progress.

Miller, T. (2016). Higher education outcomes-based funding models and academic quality. Indianapolis, IN: Lumina Foundation.

Mitchell, M., Leachman, M., & Saenz, M. (2019). State higher education funding cuts have pushed costs to students, worsened inequality. Washington DC: Center on Budget and Policy Priorities.

Obergfell, M. (2018). Performance based funding is here to stay. Retrieved from https://www.newamerica.org/education-policy/edcentral/performance-based-funding-here-stay/

Tennessee Higher Education Commission. (n.d.). Overview of Outcomes-Based Funding Formula. Retrieved from https://www.tn.gov/content/dam/tn/thec/bureau/legal/focus/ OutcomesBasedFormulaNarrative_ETSU.pdf

Umbricht, M. R., Fernandez, F. & Ortagus, J. C. (2017). An examination of the (un)intended consequences of performance funding in higher education. Educational Policy, 31, 643–673.