Web-based educational technologies enable researchers to analyze student learning by applying data mining to usage patterns, predicting final grades based on logged data. Using a combination of classifiers and a genetic algorithm (GA), the study significantly improves prediction accuracy, aiding early identification of at-risk students in large classes for timely intervention.