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Social reference model for adaptive web learning

By Fawaz Ghali and Alexandra I. Cristea


In this paper, we describe the design steps of extending LAOS, a five-layer framework for generic adaptive web learning authoring, by adding a social layer to capture (and adapt) information from 1) collaborative authoring (i.e. editing the content of other learners, describing the content using tags, rating the content, and commenting on the content, etc); and 2) authoring for collaboration (i.e., adding authors' activities, such as defining groups of authors, subscribing to other authors, etc). Moreover, the paper presents MOT 2.0, an adaptive E-learning 2.0 system, which is built on the proposed reference model, and finally, we report on our evaluations to validate the new Social Layer by comparing MOT 2.0 with its predecessor, MOT 1.0

Topics: QA76
Publisher: Springer
Year: 2009
DOI identifier: 10.1007/978-3-642-03426-8_21
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