推荐系统
计算机科学
风格(视觉艺术)
情报检索
偏爱
万维网
人工智能
机器学习
数学
历史
统计
考古
作者
Vivat Thongchotchat,Kazuhiko Sato,Hidetsugu Suto
标识
DOI:10.1109/icbir52339.2021.9465832
摘要
Learning style is the preference way of learning which can be applied with recommender system to develop the computer-support learning system which can make the tailored learning path for each particular learner. This study did the systematic literature review to gain insight of gathered recently published articles involving recommender system utilizing recommender system from trustable sources; IEEE Xplore and ScienceDirect; using designed search keywords and criteria then extracted information for answering what is the most used learning style theory and recommender algorithm in recently developed recommender systems utilizing learning style. The review study found that Felder & Silverman's theory has been the most used theory with 72.5% of all reviewed articles and suitable application is the most used recommender algorithm with 42.5% of all.
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