KnowledgeTree: a distributed architecture for adaptive e-learning
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
Dynamic assembly of learning objects
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
Personalization in distributed e-learning environments
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
Personalized web exploration with task models
Proceedings of the 17th international conference on World Wide Web
Adaptive Navigation Support for Open Corpus Hypermedia Systems
AH '08 Proceedings of the 5th international conference on Adaptive Hypermedia and Adaptive Web-Based Systems
Re-assessing the Value of Adaptive Navigation Support in E-Learning Context
AH '08 Proceedings of the 5th international conference on Adaptive Hypermedia and Adaptive Web-Based Systems
AH '08 Proceedings of the 5th international conference on Adaptive Hypermedia and Adaptive Web-Based Systems
Communities and Emerging Semantics in Semantic Link Network: Discovery and Learning
IEEE Transactions on Knowledge and Data Engineering
Personal Readers: Personalized Learning Object Readers for the Semantic Web
Proceedings of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology
NavEx: Providing Navigation Support for Adaptive Browsing of Annotated Code Examples
Proceedings of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology
Proceedings of the 13th ACM/IEEE-CS joint conference on Digital libraries
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Web based intelligent learning systems are coming out as one the most important research issue in the e-learning area. However, two main cognitive problems are confronted by the intelligent learning systems which are caused by the self-controlled mechanism. To solve this problem, learning path is proposed by many systems, however, learners' learning characteristics, such as their learning styles are still omitted by the most learning systems. This paper proposed an intelligent learning system called Smap, whose learning objects are organized in a 3- dimensioned semantic map. The final goal of Smap is to provide learners with their personalized learning path according to their different learning styles.