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Title:
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PERSONALIZING M-LEARNING SYSTEMS USING RECOMMENDER SYSTEMS |
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Author(s):
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Mahsa Baniardalan, Mehregan Mahdavi |
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ISBN:
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978-972-8939-55-7 |
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Editors:
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Piet Kommers, Ji-ping Zhang, Tomayess Issa and Pedro Isaías |
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Year:
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2011 |
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Edition:
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Single |
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Keywords:
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Customization, Recommender system, Mobile learning, Context aware |
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Type:
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Short Paper |
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First Page:
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226 |
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Last Page:
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230 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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In mobile learning, there is no limitation for the number of learners; it is more attractive than traditional learning, more convenient and cheaper for updating, quicker in terms of broadcasting, less bulky and it is easier to transfer information. In addition, the studies show that today, personalization is an important prerequisite for attracting learners in order to consider their requirements and interests and to provide proper context for the learners. This can result in improving the level of learning. In this paper, a comprehensive model is presented which includes personal, contextual, and environmental properties. Based on these parameters, the recommender system suggests educational material in a proper pattern such that the learner is attracted to the learning system and the systems feedback can be tested using questionnaire. |
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