Towards Effective Automatic Feedback for Simulator Training

Abstract

The presence of an expert instructor during simulator training is of great importance for the trainees, if not indispensable. The instructor’s role is to give feedback and guide the trainees to help them make the right decisions on time as effectively as possible. The instructor starts or pauses the training scenarios when needed and facilitates reflection during and after the scenarios. However, the fact that simulator-training sessions are very dependent on the participation of a guiding instructor can be a drawback, since there are not always sufficient expert instructors to fulfil the training demands. In this work, an intelligent tutoring system (ITS) is proposed as an automatic feedback solution for simulator training. It is based on effective assessment of the system conditions using a clustering based anomaly detection technique as a core component. Furthermore, we provide insights into the design of a proper interface for our ITS. The article presents the methodology for developing such a system which consists of three stages: data collection, data analysis and delivering feedback.