The complex relationship between financial aid packages and enrollment numbers creates conflict between different goals within higher education institutions. These priorities often include maximizing revenue from tuition, increasing the numbers of underrepresented students enrolled, and maintaining or increasing graduation rates. However, recent reporting has called into question the rising trend of using algorithms to choose which students to accept and how much aid to give. Are the digital transformation of enrollment and financial aid decisions positive steps? As institutions plot a course in digitizing decision-making, they need to be aware of the possible pitfalls to avoid unintended consequences down the road.
Competition for Students and Revenue
Colleges and universities seek to maximize student enrollment and tuition revenue, both goals supporting the future health of the institution. But while competing against each other for a limited pool of both students and money, colleges have different methods to achieve the greatest possible yield of enrolling students and the highest tuition revenue. In the process, it is easy for students’ prospects of graduating to fall by the wayside. Thus, institutions may not be prioritizing the best outcomes for long-term institutional soundness.
Higher education has overall goals of graduating the highest percent of enrolling students, enrolling the most underserved students, and supporting them through graduation. In other words, the loftiest ideals of education are to provide the fruits of knowledge for the betterment of both individuals and society. The more immediate goals of individual institutions can conflict with the higher good. It remains as complex as ever to reconcile the priorities and set policy, both institutional and national, to serve immediate and longer-term goals. The more we learn, the more questions arise in determining the best course forward. `
The Pitfalls of Algorithms in Higher Education
The use of algorithms to determine how to get the most students to enroll while maximizing revenue is particularly in question. A report from the Brookings Institution’s Artificial Intelligence and Emerging Technologies Initiative points to troubling trends in using algorithms as a tool to achieve goals in the admissions and financial aid decisions that higher education institutions make. For example, suppose the algorithms help colleges to offer the lowest financial aid that will induce the largest number of students to enroll. In that case, they may be offering just barely enough assistance to get students into the school, yet the students may need more support to persist until graduation. Though trying to maximize revenue through giving the minimum amount of aid may seem like a sound financial strategy for schools, if it results in fewer students graduating and higher debt loads for students overall (both drop-outs and graduates), this can hurt institutional reputation in the long run.
Financial Aid and Graduation
While examining the process of decisions on financial aid offers to accepted students, it is difficult but necessary to find ways to prioritize student success. While a smaller package of financial assistance may be enough to tempt students to enroll, they are more likely to drop out if they run into financial hardships as they go through their studies. Making sure initial financial aid packages are adequate, especially for students most at-risk of not reaching graduation, can help set students up for better success through the stressful process of studying and continuing to afford their studies.
Another problem with the financial aid process is that students may not fully understand the financial terms of the aid package. The American Talent Initiative, a consortium of four-year colleges and universities committed to increasing the number of low- and moderate-income students enrolled and graduated, has offered best practices to make aid offers more understandable to potential students. Considering that transparency in lending for consumer protection is required in many realms of finance, transparency in the college aid process seems essential. Clear financial expectations and understanding can help lower-income and underserved students persist through graduation.
Navigating the Intersection of Enrollment Yield and Financial Aid
While technology in the form of algorithms promises more easily fulfilling institutional goals, it can have unintended consequences. Algorithms are only as good as the humans who design them, and oversight and analysis of options must be part of every process. For example, while recommendations to keep financial aid needs out of the acceptance decision process, the calculations on financial aid may benefit more from the detailed projections of algorithms. But evaluating how financial aid will impact enrollment and graduation needs to be included in the decision-making process. Though financial distress is just one metric in the complex web of reasons students fail to graduate, any help in the institution-wide effort to support especially the most vulnerable students to persist is needed. Admissions and financial aid can work together to meet the many goals of the college while also supporting institutional and national initiatives to maximize graduation rates.