Fast discovery of association rules
Advances in knowledge discovery and data mining
Automatic personalization based on Web usage mining
Communications of the ACM
Real world performance of association rule algorithms
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Discretization: An Enabling Technique
Data Mining and Knowledge Discovery
What Makes Patterns Interesting in Knowledge Discovery Systems
IEEE Transactions on Knowledge and Data Engineering
Analyzing the Subjective Interestingness of Association Rules
IEEE Intelligent Systems
ELM-ART: An Intelligent Tutoring System on World Wide Web
ITS '96 Proceedings of the Third International Conference on Intelligent Tutoring Systems
Handbook of data mining and knowledge discovery
Handbook of data mining and knowledge discovery
A System for Building Intelligent Agents that Learn to Retrieve and Extract Information
User Modeling and User-Adapted Interaction
Building a Recommender Agent for e-Learning Systems
ICCE '02 Proceedings of the International Conference on Computers in Education
A graph model for E-commerce recommender systems
Journal of the American Society for Information Science and Technology
Knowledge Discovery with Genetic Programming for Providing Feedback to Courseware Authors
User Modeling and User-Adapted Interaction
Educational data mining: A survey from 1995 to 2005
Expert Systems with Applications: An International Journal
Finding association rules that trade support optimally against confidence
Intelligent Data Analysis
Data mining in course management systems: Moodle case study and tutorial
Computers & Education
Adaptive and Intelligent Web-based Educational Systems
International Journal of Artificial Intelligence in Education
Unsupervised strategies for shilling detection and robust collaborative filtering
User Modeling and User-Adapted Interaction
Case-studies on exploiting explicit customer requirements in recommender systems
User Modeling and User-Adapted Interaction
Discovering prediction rules in AHA! courses
UM'03 Proceedings of the 9th international conference on User modeling
The adaptive web: methods and strategies of web personalization
The adaptive web: methods and strategies of web personalization
Data mining for web personalization
The adaptive web
Social navigation support in a course recommendation system
AH'06 Proceedings of the 4th international conference on Adaptive Hypermedia and Adaptive Web-Based Systems
Comparison of machine learning methods for intelligent tutoring systems
ITS'06 Proceedings of the 8th international conference on Intelligent Tutoring Systems
Using rules discovery for the continuous improvement of e-learning courses
IDEAL'06 Proceedings of the 7th international conference on Intelligent Data Engineering and Automated Learning
Evaluating Web Based Instructional Models Using Association Rule Mining
UMAP '09 Proceedings of the 17th International Conference on User Modeling, Adaptation, and Personalization: formerly UM and AH
Proceedings of the 2009 conference on Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling
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
Building group recommendations in e-learning systems
KES-AMSTA'10 Proceedings of the 4th KES international conference on Agent and multi-agent systems: technologies and applications, Part I
Educational data mining: a review of the state of the art
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
SIeSTA: aid technology and e-service integrated system
ADNTIIC'10 Proceedings of the First international conference on Advances in new technologies, interactive interfaces, and communicability
CAEPIA'11 Proceedings of the 14th international conference on Advances in artificial intelligence: spanish association for artificial intelligence
Discovering and recognizing student interaction patterns in exploratory learning environments
ITS'10 Proceedings of the 10th international conference on Intelligent Tutoring Systems - Volume Part I
Rule-Based reasoning for building learner model in programming tutoring system
ICWL'11 Proceedings of the 10th international conference on Advances in Web-Based Learning
Designing a user interface to manage recommendations in virtual learning communities
International Journal of Web Based Communities
Multi-context recommendation in technology enhanced learning
ITS'12 Proceedings of the 11th international conference on Intelligent Tutoring Systems
Building group recommendations in e-learning systems
Transactions on Computational Collective Intelligence VII
An approach for LMS assessment
International Journal of Technology Enhanced Learning
iLOG: a framework for automatic annotation of learning objects with empirical usage metadata
International Journal of Artificial Intelligence in Education
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Nowadays we find more and more applications for data mining techniques in e-learning and web-based adaptive educational systems. The useful information discovered can be used directly by the teacher or author of the course in order to improve instructional/learning performance. This can, however, imply a lot of work for the teacher who can greatly benefit from the help of educational recommender systems for doing this task. In this paper we propose a system oriented to find, share and suggest the most appropriate modifications to improve the effectiveness of the course. We describe an iterative methodology to develop and carry out the maintenance of web-based courses to which we have added a specific data mining step. We apply association rule mining to discover interesting information through students' usage data in the form of IF-THEN recommendation rules. We have also used a collaborative recommender system to share and score the recommendation rules obtained by teachers with similar profiles along with other experts in education. Finally, we have carried out experiments with several real groups of students using a web-based adaptive course. The results obtained demonstrate that the proposed architecture constitutes a good starting point to future investigations in order to generalize the results over many course contents.