Abstract
Recently, various types of Social Networking Service (SNS) have been actively utilized in many educational situations, and the effectiveness has been continuously reported. The aim of this paper is to develop a web based discussion support system, to introduce the proposed system to a real university lecture, and to examine the operational policy for improving the learning effect from the viewpoint of quantitative perspective. The system of this paper offers interactivity between lecturers and students to dialogue opportunities in a PBL practical lecture. To support interactions in learning, a web application of SNS with groupware function and micro-blog based communication function similar to Twitter is developed with LAMP and Ajax, and it works as an information transmission platform for enhancing interactions and collaborative activities. All students can post their comments and questions by the form of short messages through a web browser on their own cell/smart phone or PC device under unique online name. The constructed SNS is only available within local area network, and only messages related to the contents of the lecture are accepted by the prepared operational policy. The constructed SNS continues to work not only during lecture but also after class. The process and the history of interactions continue to be stored on the virtual space, so a lecturer can get to know the condition of students such as the depth of understanding and the difficulty level of the contents, and besides, students can easily cooperate with each other. This paper prepared 3 different operational policies for each learning group, and clarified the difference between these operational policies from the viewpoint of complex network theory. Also by comparing each operational policy on the basis of subjective evaluation result and the quality of learning outcome, an efficient operational policy to promote SNS blended learning was clarified. Additionally, the characteristics of SNS utilization according to student's learning outcome were shown with principal component analysis.
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More From: International Journal of Knowledge and Systems Science
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