Conceptual Framework of a Synthesized Adaptive e-Learning and e-Mentoring System Using VARK Learning Styles with Data Mining Methodology

Abstract

Currently, e-learning systems are becoming more popular. This is because e-learning systems provide learners freedom to study with unlimited time and at any location. But, most of the e-learning systems present the same learning content without regard to different learning styles of learners. Many learners have to adapt to different learning styles such as learning content from images which is not specifically targeted at their needs. Meanwhile, other learners may have aptitude in reading or from listening, etc. Therefore, learning and teaching processes are important issues that teachers need to adjust their teaching according to individual learners. If each learner obtains content that aligns with their own learning style, it will lead to more achievement. The purpose of this research is to synthesize the learning model of adaptive e-learning and e-mentoring system in order to recommend learners and analyze the VARK learning style (VARK is an acronym for visual, aural, read/write, and kinesthetic) by using data mining methodology. The synthesized model consists of four modules which are 1) esaB eluR KRAV eludoM2) VARK Learner Module 3) Content Module and 4) Learning Module.