Course Load

Course load research aims to accurately quantify the actual workload students experience in their academic programs, moving beyond simple credit hour counts. Current studies utilize machine learning models, trained on learning management system data and enrollment patterns, to predict perceived course workload and analyze its impact on student success, particularly retention. These findings highlight discrepancies between perceived and credit-hour-based workload, especially in STEM fields, informing improved academic advising strategies and more effective student support systems.