Technological innovations have expanded the parameters of what we thought artificial intelligence (AI) could do. Many experts believe AI is quietly disrupting higher education’s administrative, teaching, learning, and research activities.
AI systems, including chatbots, text editors, and learning management systems, can help admissions officers make more informed selection decisions.
For example, StudentSelect.AI is an intelligence engine that delivers deep insights into applicant data that schools have already collected. This algorithm goes beyond GPA and test scores to gain deeper insights about applicants and helps schools make more informed admissions decisions.
AI Supports The Admissions Process
AI tools are being used to crunch data on recruitment, admission, and retention, to aid in decision-making processes, and to assess productivity and performance.
The recent AI uptake in the academic space is likely due to tighter budgets and reduced reliance on standardized testing.
But AI and machine learning (ML) considerably combat these barriers by helping leaders leverage resources more effectively and make better overall decisions. Emily Campion, Ph.D., assistant professor in management at the University of Iowa, told Student Select AI in a recent interview that individuals and institutions will likely be intelligent consumers of this technology.
“AI is beneficial in two key ways,” Campion stated. “First, it's helpful when tasks are repetitive, frequently performed, and time-consuming. And the second way AI can be helpful is to synthesize large amounts of information from diverse sources.”
Admissions staff receive the same questions from students about where to submit their applications or what materials they need. Chatbots are inquiry management tools, so they help manage the questions that land in your inbox.
Chatbots are great for providing certain information, such as application deadlines, links to register for an open house, where to submit your FAFSA, or even how to apply for housing on campus.
Most recently, researchers are investigating whether and how AI computer models can be trained to read college essays effectively and identify within them an applicant’s character and prosocial traits, thereby scoring “soft” or non-cognitive skills like perseverance, teamwork, and leadership on a scale from 1 to 10.
AI Predicts Student Success/ Retention
Student success plays a vital role in educational institutions, as it is often used as a metric for the institution’s performance. Early detection of students at risk, along with preventive measures, can drastically improve their success.
AI systems provide valuable insight into patterns and behaviors that make students successful.
For example, a system might notice that students who participate in extracurricular activities or have a particular learning style are more likely to succeed academically.
AI prescriptive models also consider significantly more data faster and more comprehensively than traditional what-if scenario planning. Educators can use this information to tailor their teaching methods and resources to support students better.
Aside from student success, student retention continues to be a significant challenge to academic institutions. In the US, only about 60% of full-time students graduate from their program, with most of those who discontinue their studies dropping out during their first year.
Academic performance has been identified as one of the most consistent predictors of student retention: Students who are more successful academically are less likely to drop out. However, additional research has shown the potential of predicting student dropout with the help of machine learning.
Machine learning approaches are predominantly concerned with predictive performance. Predictive analytics learns from the data it ingests, sorts through vast amounts of data, and combines that behavioral history in new ways to identify the variables that predict success.
Student Select AI uses natural language processing and machine learning to provide holistic, unbiased, and, most importantly, predictive applicant personality and competency assessments from the application essay or interview transcript.
Going far beyond traditional metrics like test scores, Student Select AI objectively measures candidates’ performance across 17 unique traits, from leadership and communication skills to analytical thinking, proactiveness, and grit.
Is your admissions program ready to move away from traditional success metrics to measure what really matters?
Schedule a live demo today to see first-hand how Student Select AI reduces time-to-decision while providing a holistic, unbiased view of each candidate and ultimately driving better admissions decisions, outcomes, and retention.
