Collaborative learning tools play important roles in communications and knowledge building, among learners in a virtual learning environment. They demand appropriate grouping algorithms as well as facilitating learners’ participations mechanisms. This paper has utilized More
Collaborative learning tools play important roles in communications and knowledge building, among learners in a virtual learning environment. They demand appropriate grouping algorithms as well as facilitating learners’ participations mechanisms. This paper has utilized some information retrieval techniquesto investigate the relevance of discussion posts to their containing forums, and extract learners’ most frequent topics. Trying to explore students online interactions, researchers have applied social network analysis, which has led to a new representation of social networking. They have proposed a new grouping algorithm based on the provided representation of social relationships. The mentioned approaches have been evaluated in some academic courses in Department of Electrical and Computer Engineering, and ELearning Center, University of Tehran. The results have revealed some considerable improvements in comparison to the traditional approaches. Research outcomes may help tutors to create and guide groups of learners more effectively.
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Today, thanks to the growth and development of communication and information technologies, online learning systems have been able to provide group learning facilities and space for interaction and exchange of ideas between learners. This requires the formation of effect More
Today, thanks to the growth and development of communication and information technologies, online learning systems have been able to provide group learning facilities and space for interaction and exchange of ideas between learners. This requires the formation of effective learning groups and the provision of learner participation tools in online learning environments, which is rarely seen in existing systems that use virtual learning centers. In this article, the content and structure of the discussion forums have been examined. Content analysis has been done in order to match the content of the discussions with the objectives of the forum and to extract the areas of interest of the participants. While expressing the achievements of the social network analysis of an academic learning environment, the researchers have presented a solution for extracting the social relationships of people through the structural analysis of discussion forums in an online learning environment. Also, they have presented a method to use the extracted relationships in the mechanisms of grouping learners and evaluated its efficiency. Different parts of this research have been conducted in different courses in consecutive semesters and its achievements can be used to improve collaborative learning activities in online and blended learning environments.
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