A Recommender Model in E-learning Environment

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• 作者：Outmane Bourkoukou ; Essaid El Bachari…
• 关键词：E ; learning ; Recommender system ; Data sets ; Collaborative filtering ; Learning objects
• 刊名：Arabian Journal for Science and Engineering
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：42
• 期：2
• 页码：607-617
• 全文大小：
• 刊物类别：Engineering
• 刊物主题：Engineering, general; Science, Humanities and Social Sciences, multidisciplinary;
• 出版者：Springer Berlin Heidelberg
• ISSN：2191-4281
• 卷排序：42

文摘

Various researches in E-learning mainly focused on improving learner achievements based on learner profile. Explosive growth of distance learning has caused difficulty of locating appropriate learning objects for learner in this environment, and it becomes relatively widespread learning method for learner. In this paper, an innovative learning approach is proposed by using recommender system to address this challenge. Based on this tool, a learning model is designed to achieve personalized learning experiences by selecting and sequencing the most appropriate learning objects. Moreover, some experiments were conducted to evaluate the performance of our approach. The result reveals suitability of using recommender system in order to support online learning activities to enhance learning.