Open AccessAdaptive Virtual Learning Environment based on Learning Styles for Personalizing E-learning System: Design and Implementation
Author(s) -
Renato R. Maaliw
Publication year - 2020
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.f8901.038620
Subject(s) - personalization , learning styles , computer science , adaptation (eye) , adaptive learning , learning environment , virtual learning environment , c4.5 algorithm , personalized learning , multimedia , virtual machine , decision tree , human–computer interaction , instructional simulation , synchronous learning , educational technology , virtual reality , artificial intelligence , cooperative learning , teaching method , world wide web , mathematics education , open learning , support vector machine , psychology , operating system , neuroscience , naive bayes classifier
Most virtual learning environment fails to recognize that students have different needs when it comes to learning. With the evolving characteristics and tendencies of students, these learning environments must provide adaptation and personalization features for adaptive learning materials, course content and navigational designs to support student’s learning styles. Based from the data mining results of learner behavioral features of five hundred seven (507) tertiary students, an accurate model for classification of student’s learning styles were derived using J48 decision tree algorithm. The model was implemented in a prototype using a framework and a proposed system architectural design of an adaptive virtual learning environment. The study resulted in the development of an adaptive virtual learning environment prototype where learner’s preferences are dynamically diagnosed to intelligently personalize the course content design and user interfaces for them.