Journal of Engineering and Applied Sciences
ISSN: Online 1818-7803ISSN: Print 1816-949x
Abstract
A learning style refers to the way an individual learns. The traditional way to identify learning styles is through a questionnaire or survey. Despite being reliable these instruments have several shortcomings that hinder the learning style identification such as students are unmotivated to fill out a questionnaire and reluctant to provide information. Thus, to solve these problems, researchers have proposed several approaches to automatically detect learning styles. The automatic detection of learning styles is proven to be beneficial to students as it can supply them with learning materials according to their individual preferences. In this study we propose a hybrid approach that combines fuzzy logic and case-based reasoning method to classify students according to their learning styles and preferences. In the context of modeling the learning styles, a student model will be constructed based on the information of student’s performance during the online course, personality and their gender. Within this study, we intend to outline our proposed model following the felder-silverman model of learning styles and the Big Five model of personality.
How to cite this article:
Nor Rahayu Ngatirin, Zurinahni Zainol and Nur`Aini Abdul Rashid. Fuzzy Case-based Approach for Detection of Learning Styles:
A Proposed Model.
DOI: https://doi.org/10.36478/jeasci.2018.321.327
URL: https://www.makhillpublications.co/view-article/1816-949x/jeasci.2018.321.327