Beckmann, JenniferBertel, SvenZander, SteffiButz, AndreasKoch, MichaelSchlichter, Johann2017-11-222017-11-222014978-3-11-034448-6https://dl.gi.de/handle/20.500.12116/7544Adaptive 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.eneLearning PlatformsUser MotivationUser SatisfactionInter-Individual DifferencesLearning StylesAdaptivität und BenutzermodellierungGender und Diversity im DesignText/Workshop Paper