Presentation Schedule
Early Indicators of Achievement: Analyzing Foundational Course Performance to Predict Student Success in Business Education (106660)
Session Chair: Ming Chen
Sunday, 10 May 2026 12:00
Session: Session 1
Room: Room G410 (4F)
Presentation Type: Oral Presentation
This study develops predictive models to estimate the likelihood of timely graduation among undergraduate students in the College of Business at a public university in California. Using an institutional dataset that integrates student demographic characteristics with detailed academic records, we focus on performance in key foundational courses as early indicators of academic progression. Multiple predictive modeling approaches are employed to estimate the probability that a student will graduate within a specified time window. In addition to prediction, we demonstrate how these models can be used to evaluate the effectiveness of student support initiatives by predicting the outcomes under different scenarios. The proposed framework enables administrators to identify students at risk of delayed graduation and to assess the impact of targeted interventions. By providing data-driven insights into student success and resource utilization, this approach supports more effective allocation of academic support resources and informed decision-making in higher education institutions.
Authors:
Ming Chen, California State University Long Beach, United States
Jasmine Yur-Austin, California State University Long Beach, United States
About the Presenter(s)
Dr. Ming Chen is a Professor of Operations and Supply Chain Management at California State University Long Beach.
See this presentation on the full schedule – Sunday Schedule
Conference Comments & Feedback
Place a comment using your LinkedIn profileShare this Presentation
Comments
Powered by WP LinkPress