Multi-agents for Simulate Preferences of Students in LO Selection

The selection of educational material that allows to address the diversity of students in the class-room is a problem faced by teachers in their daily work. The difficulty increases as you wish to attend to a greater number of traits in the trainees, for example, their predominant learning styles and their conditions of disability, to cite some cases. A valid alternative to include different profiles of students and to evaluate the type of materials available is to simulate students with different characteristics and evaluate the relevance of available educational resources. This article presents an interactive tool that supports the teacher in this task, simulating the behavior of students through agents, providing each one with different learning styles and special education needs related to any disability condition. The multi-agent system recommends learning objects (LO) stored in a repository, according to the preferences of agents, which were guide by rules defined according to their characteristics and associated with the metadata of the resources. The appropriate materials are chosen for all students selected by the teacher.