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Towards adaptation in e-learning 2.0

Authors
Publisher
Taylor & Francis Ltd.
Publication Date
Keywords
  • Qa76 Electronic Computers. Computer Science. Computer Software
Disciplines
  • Design
  • Education

Abstract

Web 2.0 is potentially a great force that can generate a vast wealth of knowledge, based on the collection of information from different individuals and communities, effectively representing a collective intelligence. This paper presents several essential steps from of an overall study on shaping new ways of learning and teaching, by using the synergetic merger of three different fields: Web 2.0, e-learning, and adaptation (in particular, personalization to the learner). These novel teaching and learning ways – the latter the focus of this paper - are reflected in and finally adding to various versions of the My Online Teacher 2.0 (MOT 2.0) adaptive system. In particular, this paper focuses on a study of how to more effectively use and combine the recommendation of peers and content adaptation to enhance the learning outcome in e-learning systems based on Web 2.0. In order to better isolate and examine the effects of peer recommendation and adaptive content presentation, we designed experiments inspecting collaboration between individuals based on recommendation of peers who have greater knowledge, and compare this to adaptive content recommendation, as well as to ‘simple’ learning in a system with a minimum of Web 2.0 support.

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