Using Semantic Web Technologies to Analyze Learning Content
IEEE Internet Computing
Computer
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Today's technology enhanced learning practices cater to students and teachers who use many different learning tools and environments and are used to a paradigm of interaction derived from open, ubiquitous, and socially-oriented services. In this context, a crucial issue for education systems in general, and for ITSs in particular, is related to the ability of leveraging these new paradigms for creating, maintaining and sharing the knowledge that these systems embed. This will enable learning environments to benefit from shared information from disparate systems, which is related to learning content and student activities, so that the overall complexity of system development and maintenance would be reduced while at the same time improving the capability of personalization, context-awareness, collaboration, and feedback provisioning. In this paper, we investigate how the Social Semantic Web can be leveraged for enabling and easing this process. This paper analyzes each ITS module, showing how it can benefit from the Social Semantic Web paradigm.