Adaptivity based on Felder-Silverman Learning Styles Model in E-Learning Systems

Adaptivity in e-learning systems can be provided by efficient modeling of the learners. Learners are modeled based on their individual needs, differences and preferences. In this context, learning styles models are generally used for adaptivity purposes, as they model how the users learn in an effective way. Felder and Silverman learning styles model is the most widely used learning styles model in the e-learning field. How this model can be used to provide adaptivity in e-learning systems is an important research subject. In this paper, this research subject is investigated, by using recent studies on learning styles based adaptive e-learning systems as the basis of the paper. The findings reveal that there are two main research fields in this area; the automatic classification of learners by their learning styles and application of learning styles models to provide adaptive e-learning systems. Some of the research areas that need to be supported with further research studies include; evaluation of the contribution and performance of different data sources and attributes used in learning styles prediction models and tools; and comparison and combination of different techniques and technologies used to develop frameworks to detect learning styles and to provide adaptivity. Therefore, it can be concluded that more research is needed to fully realize the potential of adaptive e-learning systems based on Felder and Silverman learning styles model, both for proposing novel learning style prediction models and developing new adaptive e-learning systems.