Application of PageRank Technique in Collaborative Learning

Authors:
Shenggang Yang;Jianmin Zhao;Xueyan Zhang;Limei Zhao
Affiliations:
Department of Automation, Institute of Electrical Engineers, Yanshan University, Qinhuangdao, P.R. China 066004;College of Mathematics, Physics and Information Engineering, Zhejiang Normal University, Jinhua, P.R. China 321004;Information Technology Department, Ningbo Radio & TV University, Ningbo, P.R. China 315020;Information Technology Department, Ningbo Radio & TV University, Ningbo, P.R. China 315020
Venue:
Advances in Blended Learning
Year:
2008

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Abstract

With the rapid development in web 2.0, lots of realm communities provide free platforms for users to enrich their knowledge through online communication, sharing and socializing without boundaries. As an on-line system may interact with thousands of users, it is almost impossible for the field experts or teachers to give instant help manually, which is not only inefficient, but also human laborious. To cope with it, an E-learning community should construct an efficiency knowledge acquiring mechanism. To assure this mechanism, this research applies PageRank-based mechanism to rank knowledge items synthetically. The system appraises the knowledge items provided by learners based on their rank, other users remarks and most importantly teachers' and realm experts' remarks, thus picks out the KIs to the knowledge base. In return the users' grade will be upgraded or degraded by their KIs. Learners are served with knowledge that best matches their needs and encouraged by each other. Thus this study sets up an aspiring and aggressive collaborative learning environment. Experiments results have shown that the developed system.