Provides a comprehensive research review of intelligent techniques for personalization of e-learning systems
Examines the incorporation of a recommender system based on collaborative tagging techniques in a tutoring system
Presents a new approach to perform effective personalization based on Semantic web technologies achieved in a tutoring system
Observes the explicit conceptualization of system components in a form of ontology facilitates knowledge sharing, knowledge reuse, communication and collaboration and construction of knowledge rich and intensive systems
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.
Part I Preliminaries.- Part II E-Learning Systems Personalization.- Part III Semantic Web Technologies in E-Learning.- Part IV Case Study: Design and Implementation of Tutoring System.- Part V Evaluation and Discussion.
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 is a collection of chapters that link together to form a comprehensive examination of how to personalize an e-learning experience. There are five parts; each part is self-contained and leads the reader onto the next logical topic. ... it should be important reading for those involved in advanced e-learning systems. The knowledge contained in these pages demonstrates the future of education and e-learning in particular.” (S. M. Godwin, Computing Reviews, November, 2016)
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 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.
Part I Preliminaries.- Part II E-Learning Systems Personalization.- Part III Semantic Web Technologies in E-Learning.- Part IV Case Study: Design and Implementation of Tutoring System.- Part V Evaluation and Discussion.
"This is a collection of chapters that link together to form a comprehensive examination of how to personalize an e-learning experience. There are five parts; each part is self-contained and leads the reader onto the next logical topic. ... it should be important reading for those involved in advanced e-learning systems. The knowledge contained in these pages demonstrates the future of education and e-learning in particular." (S. M. Godwin, Computing Reviews, November, 2016)
Inhaltsverzeichnis
Part I Preliminaries.- Part II E-Learning Systems Personalization.- Part III Semantic Web Technologies in E-Learning.- Part IV Case Study: Design and Implementation of Tutoring System.- Part V Evaluation and Discussion.
Klappentext
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.
Provides a comprehensive research review of intelligent techniques for personalization of e-learning systems
Examines the incorporation of a recommender system based on collaborative tagging techniques in a tutoring system
Presents a new approach to perform effective personalization based on Semantic web technologies achieved in a tutoring system
Observes the explicit conceptualization of system components in a form of ontology facilitates knowledge sharing, knowledge reuse, communication and collaboration and construction of knowledge rich and intensive systems
