Artificial intelligence and tutoring systems: computational and cognitive approaches to the communication of knowledge
Foundations of distributed artificial intelligence
Foundations of distributed artificial intelligence
User Modeling and User-Adapted Interaction
IEEE Internet Computing
Workflow and End-User Quality of Service Issues in Web-Based Education
IEEE Transactions on Knowledge and Data Engineering
IEEE Intelligent Systems
Designing Distributed Learning Environments With Intelligent Software Agents
Designing Distributed Learning Environments With Intelligent Software Agents
Design and Implementation of a Distributed Learning Resource Registry System
CIT '04 Proceedings of the The Fourth International Conference on Computer and Information Technology
ISABEL: A Multi Agent e-Learning System That Supports Multiple Devices
IAT '07 Proceedings of the 2007 IEEE/WIC/ACM International Conference on Intelligent Agent Technology
An application of intelligent techniques and semantic web technologies in e-learning environments
Expert Systems with Applications: An International Journal
Advanced ontology management system for personalised e-Learning
Knowledge-Based Systems
Machine learning based learner modeling for adaptive web-based learning
ICCSA'07 Proceedings of the 2007 international conference on Computational science and its applications - Volume Part I
User modeling for adaptive e-learning systems
ICCSA'12 Proceedings of the 12th international conference on Computational Science and Its Applications - Volume Part III
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The use of one-size-fits-all approach is getting replaced by the adaptive, personalized perspective in recently developed learning environments. This study takes a look at the need of personalization in e-learning systems and the adaptivity and distribution features of adaptive distributed learning environments. By focusing on how personalization can be achieved in e-learning systems, the technologies used for establishing adaptive learning environments are explained and evaluated briefly. Some of these technologies are web services, multi-agent systems, semantic web and AI techniques such as case-based reasoning, neural networks and Bayesian networks used in intelligent tutoring systems. Finally, by discussing some of the adaptive distributed learning systems, an overall state of the art of the field is given with some future trends.