Ontology matching processes steered by heuristic rules on learning style profiling of a novel architecture serving LMSs in realizing personalized learning paths
Abstract
Although, until now, LMS have greatly beneficiated through multiple channels, from ICT enhancements to provide adaptation, the rendering of personalized learning paths has not entirely been investigated. In this article we present an architecture and a personalization algorithm, which can be layerly applied even in the structures of already established LMS, and can provide personalized educational resources. This architecture is based on semantic-web technologies to describe the entities (i.e. learners and learning resources) of the LMS and on learning styles for their appropriate personalized matching. A prominent outcome of our proposal is the tactile description of the properties of the educational resources so as they are able to highlight their educational capabilities. This promotion is significantly useful towards the learning objects’ most suitable selection in an efficient educational process, as well as, their sharing among learning management platforms.
Article Details
- Section
- Editorial
Authors retain copyright under a Creative Commons Attribution Non-Commercial License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in the proceedings.
