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Title:
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A ROUGH SET APPROACH TO PERSONALIZATION IN WEB-BASED LEARNING SYSTEMS |
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Author(s):
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Kittisak Kerdprasop , Nittaya Kerdprasop |
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ISBN:
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978-972-8924-58-4 |
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Editors:
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Miguel Baptista Nunes and Maggie McPherson (series editors: Piet Kommers, Pedro Isaías and Nian-Shing Chen) |
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Year:
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2008 |
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Edition:
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V I, 2 |
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Keywords:
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Personalization, rough set, web-based learning. |
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Type:
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Full Paper |
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First Page:
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60 |
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Last Page:
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67 |
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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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We propose an environment to support the development of web-based learning systems. Primary function of the system
is to manage the learning process as well as to generate content customized to meet a unique requirement of each learner.
Among the available supporting tools offered by several vendors, we propose to enhance the learning systems'
functionality to individualize the presented content with the knowledge induction ability. Our induction technique is
based on rough set theory. The induced rules are intended to be the supportive knowledge for guiding the content flow
planning. They can be used as decision-support rules to help content developers on managing content delivered to
individual learner. The proposed method has been explained via an algorithm and a running example. |
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