User Modeling and User-Adapted Interaction
High-Level Student Modeling with Machine Learning
ITS '00 Proceedings of the 5th International Conference on Intelligent Tutoring Systems
Building a Recommender Agent for e-Learning Systems
ICCE '02 Proceedings of the International Conference on Computers in Education
Authoring of learning styles in adaptive hypermedia: problems and solutions
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Naive Bayes models for probability estimation
ICML '05 Proceedings of the 22nd international conference on Machine learning
Educational data mining: A survey from 1995 to 2005
Expert Systems with Applications: An International Journal
Evaluating Bayesian networks' precision for detecting students' learning styles
Computers & Education
Adaptive and Intelligent Web-based Educational Systems
International Journal of Artificial Intelligence in Education
Using Clustering Technique for Students' Grouping in Intelligent E-Learning Systems
USAB '08 Proceedings of the 4th Symposium of the Workgroup Human-Computer Interaction and Usability Engineering of the Austrian Computer Society on HCI and Usability for Education and Work
User Modeling and User-Adapted Interaction
Inferring learning and attitudes from a Bayesian Network of log file data
Proceedings of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology
Student Groups Modeling by Integrating Cluster Representation and Association Rules Mining
SOFSEM '10 Proceedings of the 36th Conference on Current Trends in Theory and Practice of Computer Science
A novel resource recommendation system based on connecting to similar e-learners
ICWL'05 Proceedings of the 4th international conference on Advances in Web-Based Learning
Personalized links recommendation based on data mining in adaptive educational hypermedia systems
EC-TEL'07 Proceedings of the Second European conference on Technology Enhanced Learning: creating new learning experiences on a global scale
Building context-aware group recommendations in E-learning systems
ICCCI'11 Proceedings of the Third international conference on Computational collective intelligence: technologies and applications - Volume Part I
Building group recommendations in e-learning systems
Transactions on Computational Collective Intelligence VII
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Building groups of students of similar features enables to suggest teaching materials according to their member needs. In the paper, it is proposed the agent-based recommender system, which, for each new learner, suggests the student group of similar profiles and consequently indicates suitable learning resources. It is assumed that learners may be characterized by cognitive styles, usability preferences or historical behavior, represented by nominal values. It is considered to build recommendations by using Naïve Bayes algorithm. The performance of the technique is validated on the basis of data of learners described by cognitive traits such as dominant learning style dimensions. Tests are done for real data of different groups of similar students as well as of individual learners.