Diagnosing Students' Learning Style in an Educational Hypermedia System

Abstract

Individualizing the learning experience for each student is an important goal for educational systems and accurately modeling the learner is the first step towards attaining this goal. This chapter addresses learner modeling from the point of view of learning styles, an important factor for the efficiency and effectiveness of the learning process. A critical review of existing modeling methods is provided, outlining the specificities and limitations of current learning style based adaptive educational systems (LSAES). The controversy regarding the multitude of partially overlapping learning style models proposed in the literature is addressed, by suggesting the use of a complex of features, each with its own importance and influence (the so called Unified Learning Style Model). An implicit modeling method is introduced, based on analyzing students’ behavioral patterns. The approach is validated experimentally and good precision rates are reported.