Learning Method Recommendation Based on VARK Model Using Certainty Factor Algorithm

Abstract

In lecture activities, students are required to master several courses that have been determined based on their respective majors. In the learning process, students often have difficulty understanding lecture material. One factor is the mismatch between how students learn and the type of learning style of each student. It is important for each student to know their respective learning styles so that in the learning process can understand the material to the fullest. One way to find out the type of student learning style is with VARK modalities (Visual, Auditory, Read/Write, and Kinaesthetic). The VARK model classifies learning style types into four types. Everyone must have all four types of learning styles, but there must be one of the most dominant. By knowing the type of learning style, students can determine how to learn according to the type of learning style. This recommendation system is implemented using Certainty Factor algorithms involving the expertise of a psychologist in it, this system is built in the website platform. The system achieves an accuracy of 94.52%, so it is good enough to provide recommendations on how to learn properly for users.