A Systematic Literature Review Enhanced Felder Silverman Learning Style Models (FSLSM)

Abstract

Student's learning style was identified and considered a critical factor in personalizing the learning process to meet student's learning preferences, specifically in intelligent e-learning system development. Learning style theories state the importance of student's profiles during learning. One of them is Felder-Silverman Learning Style Model (FSLSM). However, FSLSM has a lack of comprehensive literature review about how to improve intelligent e-learning system performance. Thus, this study analyzed and classified prior studies between 2011 and 2020 regarding FSLSM implementation and intelligent e-learning system development, including the trend. This study categorized several techniques found: identification system technique, recommendation system technique, recommendation learning object, and evaluation system technique. This study shows that FSLSM enhancement in e-learning may improve system quality using a recommendation technique. Furthermore, combining identification, recommendation, and evaluation system techniques may improve the effectiveness and efficiency of the learning process in an intelligent e-learning system.