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.
Index Terms—E-learning, adaptive learning, learning style,
VARK learning style.
The authors are with the Faculty of Information Technology, King
Mongkut’s University of Technology North Bangkok, Bangkok, Thailand
(e-mail: ammubon@hotmail.com, monchai@kmutnb.ac.th).
[PDF]
Cite:Oranuch Pantho and Monchai Tiantong, "Conceptual Framework of a Synthesized Adaptive e-Learning and e-Mentoring System Using VARK Learning Styles with Data Mining Methodology," International Journal of Computer Theory and Engineering vol. 7, no. 4, pp. 316-319, 2015.
