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A Network Analysis Method for Selecting Personalized Content in e-Learning Programs

Academic programs demand a constant updating. As the reader might agree, today's societies demand a new merge of knowledge elements. Current web-infrastructure is able to support new approaches in science development. On the one hand, due to current social, scientific and technological advances, academic programs in universities are clearly under pressure to be constantly restructured and renewed in order to provide valid and up-to-date knowledge to students. On the other hand, students obviously have different academic needs and backgrounds. So every person needs to follow a specific path in its training process. Our approach aims at proposing a well-ordered method for selecting personalized contents in e-Learning environments through the use of complex network analysis. Due to the similar nature and structure of knowledge and despite the diversity of knowledge types, the proposed method could be easily extrapolated to different academic programs and even account for some diversity in human profiles.