Intelligent systems to support the active self-learning in industrial automation

Laboratory work and experimentation is the most important cornerstone in engineering education. However often times there are not resources enough in the laboratories of industrial automation, or enough time to apply the knowledge acquired in lectures. Therefore, it is necessary to have support systems that enable students to learn in an autonomous way and teach them in the management of physical resources available in the laboratory. This paper describes an intelligent educational system based on adaptive tests, concept maps and simulations of a FESTO educational training plant, as a proposal to improve the teaching and learning of the subject of Advanced Industrial Automation.