learning styles, e-learning, data mining analysis

In adaptive e-learning we try to make learning more efficient by adapting the process of learning to students' individual needs. To make this adaptation possible, we need to know key students characteristics - his motivation, group learning preferences, sensual type and various learning styles. One of the easiest ways to measure these characteristics is to use questionnaires. New questionnaire was created because there was no questionnaire to measure all these characteristics at once. This questionnaire was filled by 500 students from different fields of study. These results were analyzed using clustering, decision tree and principal component analysis. Several interesting dependencies between students' properties were discovered using this analysis.