Thriving in a Higher Education Landscape of Change: New Applications for Artificial Intelligence and Machine Learning
By Chris Cruz | April 2, 2020
Due to demographic shifts and a declining birth rate, in 2026 the four-year-college student population is predicted to start shrinking by more than a quarter of a million a year, according to Carleton College economist Nathan Grawe. But even as the potential learner pool is decreasing, universities are struggling to stop the flood of fraudulent applications that threaten to overwhelm admissions systems. In order to survive in this turbulent marketplace, universities will need to get smarter about filtering out fake applications and understanding who their ideal prospective student is – and how to find, recruit, and retain them. That’s where artificial intelligence (AI) and machine learning (ML) can help, allowing institutions to reduce fraud, target markets, and engage with prospects, students, and alumni at a level of specificity that heretofore did not exist. Machine learning and managed AI can also help analyze trends, numbers, and patterns in order to develop solutions for forecasting, based on longitudinal data, and for recommending student interventions on a personalized level. This is precisely what’s needed to develop and improve strategies for recruitment and retention in an increasingly competitive, shrinking market. Here are two real-world examples of how higher education institutions are utilizing AI and ML to improve operations and student outcomes.
Finding Solutions for Admissions Fraud
Detecting Risk and Improving Retention