Learning Object Metadata Mapping With Learning Styles as a Strategy for Improving Usability of Educational Resource Repositories

One of the topics that generate interest in the community is the possibility of relating the characteristics of students with the type of material that best suits the student's learning style, interests, and preferences. This topic holds most importance in systems that perform automatic selection of materials and educational activities and thus improve usability. The main idea of this paper is directed to the personalized selection of learning objects according to the student learning style. The proposal and some of the tests that predict good outcomes in diverse systems are presented.