E-Learning Systems [electronic resource] : Intelligent Techniques for Personalization /
By: Klašnja-Milićević, Aleksandra [author.].
Contributor(s): Vesin, Boban [author.] | Ivanović, Mirjana [author.] | Budimac, Zoran [author.] | Jain, Lakhmi C [author.] | SpringerLink (Online service).
Series: Intelligent Systems Reference Library: 112Publisher: Cham : Springer International Publishing : Imprint: Springer, 2017Edition: 1st ed. 2017.Description: XXIII, 294 p. 126 illus., 102 illus. in color. | Binding - Card Paper |.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319411637.Subject(s): Computer Engineering
| Educational Technology | Information Systems Applications (incl. Internet) | Artificial IntelligenceDDC classification: 006.3 Online resources: Click here to access eBook in Springer Nature platform. (Within Campus only.)
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Springer Nature eBookSummary: This monograph provides a comprehensive research review of intelligent techniques for personalisation of e-learning systems. Special emphasis is given to intelligent tutoring systems as a particular class of e-learning systems, which support and improve the learning and teaching of domain-specific knowledge. A new approach to perform effective personalization based on Semantic web technologies achieved in a tutoring system is presented. This approach incorporates a recommender system based on collaborative tagging techniques that adapts to the interests and level of students' knowledge. These innovations are important contributions of this monograph. Theoretical models and techniques are illustrated on a real personalised tutoring system for teaching Java programming language. The monograph is directed to, students and researchers interested in the e-learning and personalization techniques. .
This monograph provides a comprehensive research review of intelligent techniques for personalisation of e-learning systems. Special emphasis is given to intelligent tutoring systems as a particular class of e-learning systems, which support and improve the learning and teaching of domain-specific knowledge. A new approach to perform effective personalization based on Semantic web technologies achieved in a tutoring system is presented. This approach incorporates a recommender system based on collaborative tagging techniques that adapts to the interests and level of students' knowledge. These innovations are important contributions of this monograph. Theoretical models and techniques are illustrated on a real personalised tutoring system for teaching Java programming language. The monograph is directed to, students and researchers interested in the e-learning and personalization techniques. .
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