MACHINE LEARNING ALGORITHMS FOR PREDICTING THE LEARNERS’ LEARNING STYLES

Abstract

Learning styles play a significant role in the lives of learners, when students recognize their learning style; they will be able to integrate it into their learning process. As a result, the process of learning will be easier, faster, and more successful. Understanding learning styles helps teachers design lesson plans to match the styles of their students, matching is very important when dealing with new or poor learners because at this stage they are easily frustrated. In the implementation result of this research work, simulation of the system was carried out and their results were obtained from the methodology employed. The Algorithm was implemented using Matlab programming language in designing the graphical user interface (GUI) with R software framework providing the statistical analysis and reports. A hybrid machine learning algorithm was used to determine learning styles automatically based on the students' actions. The result establishes that the classification algorithms: Naive Bayes performs better than K Nearest Neighbor when K- mode is used for clustering the data.