Title: The recommendation mechanism for social learning environment

Authors: Martin M. Weng; Jason C. Hung; Jing-De Weng; Timothy K. Shih

Addresses: Department of Computer Science and Information Engineering, Tamkang University, New Taipei City, Taiwan ' Department of Information Technology, Overseas Chinese University, Taichung City, Taiwan ' College of Management, Yang-En University, Quanzhou City, China ' Department of Computer Science and Information Engineering, National Central University, Zhongli City, Taiwan

Abstract: Although traditional e-learning has limitations of time and space, 'OpenCourseWare' further breaks through the limitations of classrooms and schools. It has given rise to a trend of online schools, with several famous universities even willing to provide credit on OpenCourseWare. However, because of the lack of help from teachers directly by online learning, it is very important for students to receive more suitable learning content for them. Other important issues include how the learning communities formed in this environment can aid in students' learning activities and how to design interactive learning mechanisms for social learning. In this research, we integrate an e-learning system with an existing social networking site, aiming to bring the power of social networks to an OpenCourseWare environment. Further, we analyse learning portfolios according to the social relationships created on social networking sites. This method provides recommendations for social learning, which can help students to choose suitable courses and engage in interactive discussion with other students.

Keywords: social learning; OpenCourseWare; recommendation systems; recommender systems; e-learning; electronic learning; online learning; learning content; learning communities; interactive learning; social networking sites; SNS; social networks; learning portfolios; social relationships.

DOI: 10.1504/IJCSE.2016.078931

International Journal of Computational Science and Engineering, 2016 Vol.13 No.3, pp.246 - 257

Received: 10 Apr 2014
Accepted: 17 May 2014

Published online: 24 Aug 2016 *

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