ITEC 2019 featured the new addition of extended abstract conference proceedings and the installment of a new Best Paper Award review process and associated subcommittee. The result is an enjoyable, high quality, and forward-leaning technical program for ITEC delegates. Ten extended abstracts and accompanying presentations out of 67 were evaluated by the Best Paper Award Committee during the conference. The winner of the Best Paper Award was the contribution that most embodied the 2019 theme of ITEC, “Interoperability by Design: Connecting People, Technology, and Nations.”
Ms Jeanine Vlasblom, R&D Engineer, NLR (Netherlands Aerospace Centre)
Jeanine Vlasblom received her Master of Science degree in Applied Cognitive Psychology at Utrecht University in 2018. She wrote her master thesis at NLR on the subject of this paper. Jeanine started as a Junior R&D Engineer at NLR's Training, Simulation & Operator Performance Department while finishing her thesis.
"Making the invisible visible - Towards increasing pilot training effectiveness by visualizing scan patterns of trainees through AR"
This paper describes the development and evaluation of a scan pattern monitoring system using augmented reality. The system enables instructors to monitor scan patterns of pilots by non-intrusively tracking the pilot’s eyes and displaying the scan patterns to the instructor through augmented reality. Subject matter experts (pilot instructors) evaluated this application as a support for the debriefing. Further development should focus on creating a tablet version for use during the debriefing and on the best ways to implement this in pilot training.
Dr Johan de Heer, Thales
Predicting Leadership during Crisis Management
Recording, modelling, analyzing human behavior is an important first step in predicting it. Here we report on a study that utilizes data mining techniques to predict leadership based on game play data. We analyzed 2700 gameplays to examine if we could find a prediction algorithm for leadership that is significant and meaningful. Our results showed an algorithm that leads to an 81% correct prediction of leadership competency, which increased the baseline by 15%. Insights derived from this study could be utilized in designing, for example, personalized learning environments.
Mr David 'Rusty' Orwin, Bohemia Interactive Simulations
Lessons learned from getting loads of people in VR for collective training
The British Army Training Capability Branch selected Bohemia Interactive Simulations to conduct a pilot study into the use of Virtual Reality (VR) in Collective Training to explore the strengths, weaknesses, opportunities, threats and benefits of VR technology and its employment. The pilot considered the effectiveness, fidelity, practicality/constraints, architecture, scale, interoperability, infrastructure and mobility of useable VR capabilities. The pilot increased in scale and complexity culminating in 37 players in VR conducting training in a company context in a combined arms battle.
Dr Robby Robson, Eduworks Corporation
Understanding how AI is applied in training: Case Studies
“Artificial Intelligence” (AI) refers to technologies that emulate human intelligence, but the term is so broad that it is often hard to tell what is meant by it, how it is applied, and what value it brings. This paper presents a framework for understanding the use of AI that clarifies inputs, outputs, the type of AI used (if any), and whether it is used to classify objects, provide recommendations, support simulations, or make decisions. The paper then illustrates the framework by applying it to use cases ranging from recommendation engines to simulations to systems that use AI to support the analysis and generation of training content.