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Descripción
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| E-Learning systems can be made more effective through personalization and adaptivity while recommending the learning content to learners. A comprehensive set of attributes needs to be identified for learner categorization to ensure personalized and adaptive content recommendation. In this paper, a set of core attributes have been identified for effectively profiling the learners and categorizing through neural networks. The learning contents have been annotated formally in ontology for recommending the personalized contents to the learners. Performance of proposed framework is measured in terms of accurate learner categorization, precise recommendation of the learning contents and completeness of ontological model. | |
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Internacional
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Si |
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JCR del ISI
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No |
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Título de la revista
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International Journal of Information and Education Technology |
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ISSN
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2010-3689 |
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Factor de impacto JCR
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Información de impacto
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Volumen
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8 |
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DOI
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10.18178/ijiet.2018.8.10.1125 |
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Número de revista
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10 |
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Desde la página
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700 |
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Hasta la página
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705 |
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Mes
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OCTUBRE |
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Ranking
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