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

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.

@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},
  volume    = {10},
  number    = {11},
  year      = {2019},
  publisher = {The Science and Information Organization},
  author    = {Jorge Luna-Urquizo},
  doi       = {10.14569/IJACSA.2019.0101188},
  url       = {https://doi.org/10.14569/IJACSA.2019.0101188}
}