Activity Plan Structure and Processing in Virtual Environments for Training Supported by Intelligent Tutoring Systems

The integration of virtual reality (VR) and intelligent tutoring systems (ITSs) in training processes has proved to be an effective option. In these systems, it is very important for ITSs to show adaptive and flexible tutoring capabilities. It must not force the student to follow strict action sequences, but to adapt itself to the unexpected -not necessarily wrong- student actions. In this work, we describe the activities structure proposed in the MAEVIF model, detailing the actions a trainee can perform, their tracking process and MAEVIF´s adaptive behavior for unexpected actions.