An adaptive educational system that caters for combination of two models of learning styles

• Main Author: Alghamdi, Abdulrahaman A.
• Other Authors: Rist, Roger : Ashton, Helen : Robertson, Judy : Marwiick, David
• Published: Heriot-Watt University 2010
• Subjects: 370.1
• Online Access: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.547666

This thesis aimed to explore the affect of combining two models of learning styles (VARK, and Honey and Mumford) in terms of students‘ learning gains and satisfaction. VARK focuses on how the students perceive learning, while Honey and Mumford examines how an individual would like to learn. A web-based educational system was built to test the combination of the two models of learning styles. A study to examine the feasibility of the system was carried out on 129 participants to explore whether the system presented tutorials according to their individual learning styles. A second study to investigate learning gains and user satisfaction was carried out on 149 participants. Satisfaction was divided into three main concepts: usability, preference and perception of learning. Learning gains were tested by giving participants a pre-test, a post-test and a confirmatory test. Participants were divided into four groups and had the lesson presented according to one learning style of either the VARK or Honey & Mumford model, both of the participants‘ learning styles or with no personal customization. The results found that participants who used the two models of learning styles showed higher learning gains and had higher levels of satisfaction across all three factors; compared to those using only one or no learning style. Furthermore, those using only one learning style showed higher learning gains and had higher levels of satisfaction than those with no learning style. The application of these findings would be of benefit to educational institutions‘ decision makers, educators, students and e-learning designers. Adaptation is a key feature of the system of research. It is intended for future work; preliminary research has shown that the users profile and learning item will change over time. This important finding is worth exploring in future research.