A Method for Detection of Learning Styles in Learning Management Systems

Each learner has his own learning style that helps him study easier. Many researchers have been concentrating in determining learners’ learning styles to aim at efficiency in implementing adaptation in learning management systems. Automatic and dynamic detection of learning style has its attractive advantages in precision and time saving. In this paper, we propose a new method that automatically estimate learners’ learning styles with respect to the FelderSilverman Learning Style Model based on their behaviors in an online course. Our first tests were compared with those obtained through the Index of Learning Style questionnaire, and it shows a promising precision in inferring learning styles and the method can be used in other LMSs.