There is considerable debate regarding whether the use of Artificial Intelligence (AI) is helping or hurting higher education. A recent report by The Brookings Institution, (Enrollment algorithms are contributing to the crises of higher education, September 14, 2021), provides what I believe is an unnecessarily negative view of the potential of AI, particularly when used constructively as a complement to human decision-making. There are many challenges facing US colleges and universities and their students (e.g., staggering student debt, lower graduation rates, a need to increase the proportion of students from underserved populations, etc.). With the proper design, oversight and ethical compass, AI can help us solve these challenges and create opportunities to improve access, affordability, and student success.
The report presented research and thoughts on the use of AI and analytics for student enrollment with a focus on how algorithms are used when admitting students and awarding financial aid in the initial phase of admissions. The report offers helpful insights, but its narrow focus does not provide a complete picture of how AI is used, its benefits, and how it can be leveraged as a tool to complement human decision-making.
AI is a “processor” that can sift through unimaginable amounts of data and present choices to the decision maker when making a variety of recruiting, enrollment, financial aid, and student support decisions.
AI helps universities understand their students better, make data-informed decisions, and therefore, support enrollment and student success goals. For enrollment decisions, AI does not replace human decision making, it complements it. AI is a “processor” that can sift through unimaginable amounts of data and present choices to the decision maker when making a variety of recruiting, enrollment, financial aid, and student support decisions.
Here are just a few reasons why AI can be an indispensable resource to help make higher education more accessible to all students and enrollment actions more equitable.
Data and advanced analytics can help colleges and universities identify different scenarios for allocating resources and can provide additional insight on how to shape a cohort that is consistent with an institution’s mission and values. Thus, predictive analytics is a tool to enhance outcomes and support decision-making.
Making financial aid decisions can be complicated. It’s not just about money; it’s about maximizing a college or university’s available financial aid resources to support student access and success and achieve institutional goals. AI — used correctly — can provide a multi-faceted view of each student, offering data and scenarios that help colleges and universities allocate aid in the most effective way possible to form a cohort that is aligned with the institution’s values. Othot’s platform is used by campuses across the country to identify which students need additional support to enroll, persist, and graduate. It also offers specific prescriptions that can be used to maximize the probability that each student will be successful.
Considering the many factors involved in decisions related to student success, it’s important to think of machine learning (a component of AI) as a processor of information — taking huge amounts of data and performing analyses that generate much-needed insights. Over and above the issues of balancing budgets, providing opportunities for students, and achieving the mission of the institution, the difficult “calculus” involving these factors is made easier with sophisticated tools. The information must be used carefully and intentionally to augment and enhance the complex human decision-making that happens every day in higher education.
Bias is a complicated “term, and it is ever present in human decision making. AI is most effective when you combine technology with human intellect and consciously work to minimize—and eventually eliminate—bias in decision making. According to my colleague, Dr. Mark Voortman, data scientist architect at Othot, “Mitigating and eliminating bias is an active journey that can be challenging, but with the right data and models it is a solvable problem.”
Ultimately, the combination of technology and human interaction is the most effective use of AI by higher education.
Find out more about how campuses are effectively using AI as part of the student journey.