Financial considerations play a significant role in the decision-making process for future first-year students pursuing a degree. “Talent is evenly distributed, but opportunity is not. It is incredibly inequitable. That is why Georgia Tech is working to provide opportunities and pathways for all students,” explained Executive Director of Strategic Student Access Rick Clark in a recent Times Higher Education Campus interview. The effort is a key part of expanding access, a focus area of Georgia Tech’s Strategic Plan. One way to achieve this goal is to leverage Institute researchers and the knowledge acquired through previous studies using machine learning techniques. With these tools, the Institute could better understand how to enhance the admissions process, streamline access to financial aid, and stay informed about student needs. 

Since 2021, the C21U team has developed predictive tools using machine learning (ML) and AI through a partnership with Tech’s Online Master of Science in Analytics (OMSA) program to provide tools to enhance the applicant selection process. The tools can help predict applicants' success in the program using various application data and comprehensive features, including letters of recommendation and statement of purpose documents. The team focused on identifying 21st-century skills and assessing leadership competencies. This data can benefit admission committees and learners alike, who can use it to tailor their professional development path. In this instance, the objective is to use AI to inform the Institute’s strategies to provide students with varied financial aid opportunities and resources. The insights gained can also guide admissions practices to promote greater accessibility and fairness. 

The study will commence with collecting extensive data during the spring semester, followed by data analysis during the fall semester of 2025 to develop comprehensive profiles to predict first-year applicants' eligibility for various financial aid categories, including Pell Grant-possible students. To create these profiles, C21U researchers will first analyze the data gathered from Tech’s Undergraduate Admissions and Financial Aid offices by the Institutional Research and Planning (IRP) team. This data encompasses personal information, academic history, test scores, and financial aid details. Advanced machine learning techniques, including natural language processing and explainable AI, will analyze the relationships between various student characteristics and their financial aid outcomes. Given the sensitive nature of the data, the research team will implement stringent security measures to safeguard student information. The data will be de-identified, encrypted, and accessible only to authorized users, ensuring security and individual student information protection.

This innovative project represents institutional advancement in using predictive analytics to improve the undergraduate admissions process and access to financial aid, and it is a collaborative effort between several Georgia Tech offices and units. These include the Center for 21st Century Universities’, Executive Director Steve Harmon, Director of Research in Education Innovation Jeonghyun (Jonna) Lee, Research Scientist Meryem Yilmaz Soylu, Postdoctoral Researcher Gayane Grigoryan, and Digital Learning Data Analyst Adrian Gallard. The study will be conducted in collaboration with Executive Director of Strategic Student Access Rick Clark, Interim Executive Director of Undergraduate Admission Mary Tipton Woolley, and Executive Director of the Office of Scholarships and Financial Aid Katie Conrad. Additionally, Institutional Research and Planning’s Senior Director Jason Wang, Data Scientist Daniel Lyczak, and the Division of Enrollment Management will contribute. While C21U will lead the study, the research team will consult with each participant unit for guidance and feedback.