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DOI: 10.14569/IJACSA.2019.0101188
PDF

Learning Management System Personalization based on Multi-Attribute Decision Making Techniques and Intuitionistic Fuzzy Numbers

Author 1: Jorge Luna-Urquizo

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 10 Issue 11, 2019.

  • Abstract and Keywords
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Abstract: The personalization of Learning Management Sys-tems is a fundamental task in the current context of e-Learning and the WWW. However, there are many controversies around the criteria used to make the selection and presentation of the most appropriate content for each user. The most used approaches in the last decade were the identification of learning styles, the analysis of the history and navigational behavior, and the classification of user profiles, without finding conclusive evidence to determine a method that can be adopted universally, consid-ering the complexity of the cognitive processes involved. This paper proposes an approach based on multi-attribute decision making techniques, which allows considering and combining the criteria most effectively used in the area, according to particular contexts, as a new approach to the content personalization and appropriate learning objects selection. The application of this approach aims to maximize the effectiveness and efficiency of the teaching process and enrich the user experience.

Keywords: Learning Management Systems (LMS); e-Learning; multi-attribute decision making; learning styles; content personal-ization; learning objects selection

Jorge Luna-Urquizo, “Learning Management System Personalization based on Multi-Attribute Decision Making Techniques and Intuitionistic Fuzzy Numbers” International Journal of Advanced Computer Science and Applications(IJACSA), 10(11), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0101188

@article{Luna-Urquizo2019,
title = {Learning Management System Personalization based on Multi-Attribute Decision Making Techniques and Intuitionistic Fuzzy Numbers},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2019.0101188},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0101188},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {11},
author = {Jorge Luna-Urquizo}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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