An Adaptable E-Learning Architecture Based on Learners' Profiling

Abstract

These days modifications and supplements to e-learning are not enough to make them successful since flexibility and adaptability is missing. Different e- Learning architecture provide different kinds of learning experience to the learners. The lack of adaptive system is due to ―One size fits for all‖ concept. Currently the research is towards to learner oriented platforms putting student motivation, habits, expectations and learning styles (additional Koper, R.; Burgos, D (2005)). The concept of adaptation has become a prominent issue in e- learning. Systems allow the users to change some system parameters and adapt their behavior accordingly is known as adaption process. Systems that adapt based on the systems assumption are called as adaptive systems (additional santally mohammed issack). Since the system adapts to a person and personalizes the learning process it can be also known as personalized system (additional Paramythis, A.; Loidl-Reisinger). So to serve the learning community better there was a necessity to profile them and identify their requirements and provide an adaptive e- learning architecture which suits the individuals needs better. So the main objective of this research was to provide an adaptive e-learning system architecture which satisfies Felder Silverman learning style. Felder- Silverman's learning model (FSLM) was chosen since FSLM synthesis of these theories can be designed to easily translate them into strategies into a university setup. Index Terms—Learning, e-Learning, Virtual Learning, e- Learning Standards, Adaptive e-learning systems.