— Currently, the conditions for learning and teaching over e-learning systems are found to be that the instructors will use lessons from pre-defined study guides. Therefore, every student will interact with the same lesson plan. Thus, performance and academic achievement of students will not be as good as it should. This is because each student has different aptitudes such as some students exceed in analysis, whereas others exceed in arts, etc. If each student receives the lesson content that matches their own aptitudes, their performance and achievement would surely increase. The goal of this research is to synthesize an adaptive e-learning recommendation system based on Multiple Intelligence and learner profiles using data mining analysis. Thus, our paper proposes a conceptual model of an adaptive e-learning guidance system based on Multiple Intelligence. The conceptual model consists of five modules. Firstly, introduction of a Rule based module. Secondly, detailed explanation of the Recommendation module for students. The third, presentation of the LMS module. The fourth, presentation of the Adaptive module. And finally, proposal of content for the module which is based on Multiple Intelligence.
— E-learning, adaptive, multiple intelligence, data mining, recommendation system.
The authors are with the Faculty of Information Technology, King Mongkut’s University of Technology North Bangkok, Bangkok, Thailand (e-mail: email@example.com, Nuttavee@kmutnb.ac.th, Sakchai@kmutnb.ac.th, Monchai@kmutnb.ac.th).
Cite: T. Kaewkiriya, N. Utakrit, S. Tangwannawit, and M. Tiantong, " A Conceptual Framework of Synthesize on an Adaptive e-Learning Guidance System Base on Multiple Intelligence," International Journal of Information and Electronics Engineering vol. 3, no. 6, pp. 622-625, 2013.