Analyzing Student Performance in Distance Learning with Genetic Algorithms and Decision Trees

Students who enrol in the undergraduate program on informatics at the Hellenic Open University (HOU) demonstrate significant difficulties in advancing beyond the introductory courses. We have embarked in an effort to analyse their academic performance throughout the academic year, as measured by the homework assignments, and attempt to derive short rules that explain and predict success or failure in the final exams. In this paper we review previous approaches, compare them with genetic algorithm based induction of decision trees and argue why our approach has a potential for developing into an alert tool.