Recommend Strategies for E-Learning 2.0 Communities

Abstract:

With the rapid progress of Web 2.0, E-Learning has evolved into E-Learning 2.0, which has been highlighted as an effective method for interactive learning. To improve the efficiency of learning, many researches focused on the personalized recommendation for knowledge sharing. However, these researches proposed the general recommendation system without considering the current knowledge sharing status in E-learning 2.0 communities. Therefore, the purpose of this study is to proposed recommend strategies according to characteristics of E-Learning communities based on social network analysis. Firstly, knowledge activity nodes in E-Learning communities are identified into four types. Secondly, based on four node types, E-Learning communities are classified into four corresponding types. Then, different recommend strategies are provided according to the types of E-Learning communities. Finally, conclusion and future research direction are discussed in the end.

• Periodical: Applied Mechanics and Materials (Volumes 568-570)
• Pages: 1547-1550
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.568-570.1547
• Online since: June 2014
• Authors: Bing Wu*, Chen Yan Zhang
• Keywords: E-Learning 2.0 Community, Knowledge Sharing, Recommend Mechanism, Social Network

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