<abstract xmlns="http://www.w3.org/1999/xhtml"><p>Traditional Learning Management Systems are installed on a single server where learning materials and user data are kept. To increase its performance, the Learning Management System can be installed on multiple servers; learning materials and user data could be distributed across these servers obtaining a Distributed Learning Management System. In this paper is proposed the prototype of a recommendation system based on association rules for Distributed Learning Management System. Information from LMS databases is analyzed using distributed data mining algorithms in order to extract the association rules. Then the extracted rules are used as inference rules to provide personalized recommendations. The quality of provided recommendations is improved because the rules used to make the inferences are more accurate, since these rules aggregate knowledge from all e-Learning systems included in Distributed Learning Management System.</p></abstract>

Traditional Learning Management Systems are installed on a single server where learning materials and user data are kept. To increase its performance, the Learning Management System can be installed on multiple servers; learning materials and user data could be distributed across these servers obtaining a Distributed Learning Management System. In this paper is proposed the prototype of a recommendation system based on association rules for Distributed Learning Management System. Information from LMS databases is analyzed using distributed data mining algorithms in order to extract the association rules. Then the extracted rules are used as inference rules to provide personalized recommendations. The quality of provided recommendations is improved because the rules used to make the inferences are more accurate, since these rules aggregate knowledge from all e-Learning systems included in Distributed Learning Management System.

Recommendation System Based On Association Rules For Distributed E-Learning Management Systems

Department of Computer Science, University of Craiova, Romania

Acta Universitatis Cibiniensis. Technical Series

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Traditional Learning Management Systems are installed on a single server where learning materials and user data are kept. To increase its performance, the...

Recommendation System Based On Association Rules For Distributed E-Learning Management Systems

Online veröffentlicht: 23. Sept. 2015

Seitenbereich: 99 - 104

DOI: https://doi.org/10.1515/aucts-2015-0072

Schlüsselwörter
association rules, educational data mining, recommendation system, LMS, e-Learning

© Mihai Gabroveanu

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Recommendation System Based On Association Rules For Distributed E-Learning Management Systems

Online veröffentlicht: 23. Sept. 2015

Seitenbereich: 99 - 104

DOI: https://doi.org/10.1515/aucts-2015-0072

Schlüsselwörterassociation rules, educational data mining, recommendation system, LMS, e-Learning

© Mihai Gabroveanu

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
association rules, educational data mining, recommendation system, LMS, e-Learning