An intelligent agent to detect learner's learning style automatically through E-learning system in Saudi Arabia - Azrilah Abdul Aziz, Alia Abdulrahman Assiri (Journal of engineering sciences and information technology, 2017)
Most of the successful conventional E-learning system lack of automatic detecting of learner learning style based on their preference. An Automatic approach marked as a better approach to characterize learning style because it is based on real student behavior. The purpose of this study is to propose a new literature-based method (Automatic approach) using intelligent agents to identify learner's learning style based on behavior using Felder-Silverman Learning Style Model (FSLSM). The new method implemented in new developed LMS. After obtaining the proposed method result, the result validates and compared with Felder-Silverman Learning Style Model questionnaire (ILS) and García method. After comparing the proposed method with the results of previous studies, the researcher got satisfactory results on precision percentage and the lowest percentage in the results was 66.6 %.