With most U.S. colleges and universities waiving SAT and ACT requirements – some making the move as a temporary response to the COVID-19 pandemic, while others, like the University of California system, upending the requirement permanently – the challenge for many institutions will be how to rethink the applicant evaluation process without this long-held and highly weighted data point.
Some schools are thinking outside the box to address the void, such as asking applicants impromptu interview questions or the University of California’s quest to develop its own substitute test that it hopes will avoid the societal criticisms associated with the SAT.
However, a growing number of institutions are exploring new ways to utilize their student data to gain new insights about prospective students, all with the aid of big data tools and emerging artificial intelligence – or AI – technology.
But what are these AI tools, and how do they work?
While AI is often thought of in pop-culture terms – as life-like robots imitating humans – it is important to understand how AI and machine learning are used.
AI is extremely useful when it comes to repetitive tasks performed frequently or time-consuming tasks. One example is online chatbots, which use AI-powered natural language processing to answer commonly asked questions from students. This, of course, alleviates having to task a human worker from manually responding to the same questions repeatedly over, say, email or phone call.
AI is also useful when it comes to synthesizing large amounts of information from diverse sources. For example, a growing use case is in the admissions process, where the technology can help admissions officers make more informed selection decisions with an expanded set of insights about their applicants.
This post would be remiss if it did not address the elephant in the room: the questions many have around AI and bias. More specifically, the concerns that AI will teach itself to become bias or perpetuate unconscious biases that might already exist in our human decisions.
That is why it is critical institutions genuinely understand how their AI tools work and engage with AI technology vendors that provide transparency into how their machine learning processes determine outcomes. It is also advisable to approach AI as a tool to expand your general understanding of your student applicants and not to outsource your decision-making.
So what are some examples of how AI can give us more insights into student applicants?
A couple of areas of promise, which are also being researched and tested at StudentSelect.AI, include the following:
Uncovering non-cognitive (NC) traits
Backed by well-researched science in text analysis, AI can reliably identify NC traits like analytical thinking, organizational skills, conscientiousness, grit, and other attributes that can paint a broader picture about an applicant. Promising applications of this type of analysis include identifying students – perhaps from disadvantaged backgrounds – who may otherwise fall short of traditional admission standards but possess NC traits that may indicate a likelihood of success.
Inclusion of program outcomes
When factoring in student outcome data, such as from students who have successfully graduated, we can start to unveil which attributes are likely indicators of future success. In the absence of test scores like the SAT, admissions deciders may need to make decisions based more heavily on “soft” factors like essays. Adding predictive indicators can help quantify what otherwise would be dependent on intuition to make these decisions.
While the above only scratches the surface on the potential of AI in higher education and, more specifically, to the admissions process, it is more important than ever that admissions leaders begin learning more about the future of technology and how institutions are adopting it.
For a deeper dive into the subject, be sure to sign up for the upcoming AACRAO webinar, De-Mystifying AI for University Admissions Leaders, on October 20, 2021, sponsored by StudentSelect.AI and hosted by Dr. Emily Campion, Ph.D.