On Small Data Sets Revealing Big Differences

We use decision trees and genetic algorithms to analyze the academic performance of students throughout an academic year at a distance learning university. Based on the accuracy of the generated rules, and on cross-examinations of various groups of the same student population, we surprisingly observe that students' performance is clustered around tutors.