doi: 10.7763/IJIET.2016.V6.685
The Design of a Rule Base for an e-Learning Recommendation System Base on Multiple Intelligences
T. Kaewkiriya
,
N. Utakrit ,
M. Tiantong
Abstract
The problem of e-learning systems, learners are given learning contents that do not match individual aptitudes. This paper aims to design a rule base for recommendations focusing on e-learning and learning profiles which are based on multiple intelligences. Design of the rule base was divided into four sections as follows. The first section covered a survey of the variables. Second section was creation of the questionnaire. Third section was a survey of the student sample groups. The last section was an analysis of data generated from the results of the survey. The process of selection for the rule base was undertaken by comparing the performance of the following algorithms 1) ID3 algorithm 2) C4.5 algorithm 3) NBTree algorithm 4) Naïve Bayes algorithm 5) Bayes Net algorithm. The C4.5 algorithm had the highest percentage of prediction. Percentage of prediction from the C4.5 algorithm equaled 83.436%.
Keywords
- E-learning
- recommendation system
- data mining
- multiple intelligence
How to Cite
T. Kaewkiriya, N. Utakrit, and M. Tiantong, "The Design of a Rule Base for an e-Learning Recommendation System Base on Multiple Intelligences," International Journal of Information and Education Technology, vol. 6, no. 3, pp. 206-210, 2016. https://doi.org/10.7763/IJIET.2016.V6.685
Copyright & License
Copyright © 2016 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).