Adaptive eLearning based on individual learning styles – Performance and emotional factors

Abstract

Adaptive eLearning systems are able to adjust to a user’s learning needs, usually by user modeling or tracking progress. Such learner-adaptive behavior has rapidly become a hot topic for eLearning. This contribution presents original research on using differ-ences in individual learning styles. Factors related to performance, motivation, satisfac-tion, and previous knowledge were targeted and used to assess the effectiveness of the approach.