Learning style model detection based on prior knowledge in e-learning system

The currently existing learning style model detection based on prior knowledge can be divided into two approaches, i.e. data-driven and literature-based approach. Both approaches are obtained by collecting data from external factors of learners. External factors are strongly affected by the behavior of learners when accessing e-learning system. On the other hand, internal factors remain unattended, e.g. prior knowledge and skills of learners. Previous researches works employed the Know Want Learn (KWL) technique to revive prior knowledge using Brainstorming and Cognitive Chart. The previous three technique are deemed being less effective and dynamic as the response remains taking a long time and highly subjective. This research proposes a method for reviving prior knowledge based on Bloom's taxonomy. We claim this method more objective as it is derived from the way of the learners acquire their knowledge and skills.