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Titlebook: Advances in Web Based Learning - ICWL 2009; 8th International Co Marc Spaniol,Qing Li,Rynson W. H. Lau Conference proceedings 2009 Springer

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0302-9743 E-learning systems, e-learning metadata and standards, educational gaming and multimedia storytelling for learning, as well as practice and experience sharing and pedagogical Issues..978-3-642-03425-1978-3-642-03426-8Series ISSN 0302-9743 Series E-ISSN 1611-3349
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https://doi.org/10.1007/978-981-10-2387-3e for experiential learning in order to provide a lasting understanding. The TCP Live learning resource allows students to explore the behavior of TCP on the global Internet, and see the wide variety of conditions that the protocol has to cope with, thereby extending their viewpoint outwith the limited scope of their own institutional firewalls.
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Enhancing the ,se of ,ooperative ,earning to ,ncrease ,velopment of ,cience Studies ,ary as facilitators to provide further co-ordination, pose questions and suggest problem-based approaches. The use of the platform secures that the teacher remains distant from the students allowing students to work by themselves and find solutions to the problems posed.
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Understanding and Facilitating Student Bloggers: Towards a Blogging Activity Modelogging activity model, which aims to reveal and explain relationships between blogging activity variables—including peer visits, commenting and posting—to achieve a better understanding of lively blog communities in courses.
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Personal Services: Debating the Wisdom of Personalisationreats posed by the capture of so much data about individuals, the implications of personalised information delivery, and whether the benefits of personalisation justify the costs. In this paper, we look at both the issues and benefits of personalisation, and consider how to steer our way to a safe and valuable use of personalisation.
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On Social e-Learning include incorporating the many of the social features of social Web sites, accounting for all key stakeholders and learning subjects, and curbing various types of misuses by people. We also examine the capabilities of representative social e-learning Web sites that are available today.
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A Machine Learning Based Framework for Adaptive Mobile Learninga framework that depicts the process of adapting learning content to satisfy individual learner characteristics by taking into consideration his/her learning style. We use a machine learning based algorithm for acquiring, representing, storing, reasoning and updating each learner acquired profile.
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