Using Genetic Algorithms for Data Mining Optimization in an Educational Web-Based System

This paper presents an approach for classifying students in order to predict their final grade based on features extracted from logged data in an education web-based system. A combination of multiple classifiers leads to a significant improvement in classification performance. Through weighting the feature vectors using a Genetic Algorithm we can optimize the prediction accuracy and get a marked improvement over raw classification. It further shows that when the number of features is few; feature weighting is works better than just feature selection. 1 Statement of problem Many leading educational institutions are working to establish an online teaching and learning presence. Several systems with different capabilities and approaches have been developed to deliver online education in an academic setting. In particular, Michigan State University (MSU) has pioneered some of these systems to provide an infrastructure for online instruction. The research presented here was performed on a p...

• Type: Conference
• Year: 2003
• Where: GECCO
• Authors: Behrouz Minaei-Bidgoli, William F. Punch
• Keywords: Education Web-based System, Educational Resources, GECCO 2003, Online