Multiagent system for learning objects retrieval with context attributes

Abstract

Educational standards that include content metadata description for materials have great potential for managing e-learning information and content units and facilitate their interoperability and reutilisation. These open semantic and distance learning aspects contribute new and important possibilities for online education systems. The Learning Objects (LOs) paradigm focuses this new gap on the management and exchange of educational materials. This paper presents an application approach to educational content recommendation based on Learning Objects. It describes an architecture based on a multi-agent system with a bio-inspired algorithm rooted in self-organisation theory. It supports the retrieval, search, selection and composition of these LOs.