Title:	ARCHITECTURE DESIGN OF A HYBRID RECOMMENDER SYSTEM IN E-LEARNING SCENARIOS
Author(s):	Christina Di Valentin, Andreas Emrich, Dirk Werth, Peter Loos
ISBN:	978-989-8704-04-7
Editors:	Philip Powell, Miguel Baptista Nunes and Pedro Isaías
Year:	2014
Edition:	Single
Keywords:	Recommender systems, context sensitive learning, social media, decision support, personalized learning.
Type:	Full Paper
First Page:	239
Last Page:	245
Language:	English
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Full Contents:	click to dowload
Paper Abstract:	Social and digital media applications have established in many settings of private and professional life. Particularly the e-learning sector would benefit from tools that foster an appropriate media integration in teaching and learning processes. The main goal of the presented research work is to increase the social media skills of all stakeholders in learning and teaching scenarios by providing them appropriate media tools, contents and recommendations of other users that are helpful in the current situation of the teaching or learning process. This paper analysis the problem field of media usage in vocational education and training and presents the architecture design and knowledge base of a recommender system in this domain. The derived architecture design and the knowledge base form the basis for recommendations about efficiently creating, using and reusing media contents in terms of an increase of social media skills. In doing so, the recommender system takes into account the user’s current context as well their current step in the working or teaching process.
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