计算机科学
人工智能
鉴定(生物学)
机器学习
过程(计算)
学习对象
主动学习(机器学习)
学习风格
推荐系统
数学教育
心理学
植物
生物
操作系统
作者
Supangat Supangat,Mohd Zainuri Saringat
标识
DOI:10.1109/icic56845.2022.10006958
摘要
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.
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