Conference article

Towards Effective Automatic Feedback for Simulator Training

Laura Marcano
Department of Electronic Engineering, Oslo and Akershus University College of Applied Sciences (HiOA), Norway

Anis Yazidi
Department of Computer Science, Oslo and Akershus University College of Applied Sciences (HiOA), Norway

Mexhid Ferati
Department of Computer Science, Oslo and Akershus University College of Applied Sciences (HiOA), Norway

Tiina Komulainen
Department of Electronic Engineering, Oslo and Akershus University College of Applied Sciences (HiOA), Norway

Download articlehttp://dx.doi.org/10.3384/ecp17138203

Published in: Proceedings of the 58th Conference on Simulation and Modelling (SIMS 58) Reykjavik, Iceland, September 25th – 27th, 2017

Linköping Electronic Conference Proceedings 138:28, p. 203-208

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Published: 2017-09-27

ISBN: 978-91-7685-417-4

ISSN: 1650-3686 (print), 1650-3740 (online)

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 systemwhich consists of three stages: data collection, data analysis and delivering feedback.

Keywords

simulator training, anomaly detection, automatic feedback, intelligent tutoring system

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