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Dynamic Adaptative Surveillance Training in a Virtual Environment Using Real-Time Cognitive Load and Performance

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DOI:

https://doi.org/10.17083/ijsg.v11i3.733

Keywords:

Dynamic Difficulty Adjustment, Adaptive Serious games, Immersive Serious Games, cognitive load, learning performance, 3D virtual environments

Abstract

Dynamic difficulty adjustment of serious games is a field of research seeking to assist participants attain an ideal learning state. To achieve this, the difficulty of a game is adjusted in real-time to approach the capabilities of the player. Many dynamic difficulty adjustment systems only measure a few variables, often solely player performance, and adjust a limited number of in-game aspects. Little research has sought to ascertain if measuring a combination of cognitive load with measures of performance in real-time leads to a more effective dynamic difficulty adjustment system. Building on research which defined ‘mental efficiency’, we conducted a novel experiment to address this gap. This is achieved by comparing two versions of a surveillance training serious game; one a linear approach and the other with our unique cognitive load and performance-based dynamic difficulty adjustment system. Our experiment included n=52 participants (26 per treatment group). The experiment demonstrates that our approach achieved similar performance outcomes with lower cognitive load, in less time than the linear difficulty approach. These results indicate that our system enhances learning capacity and may prove beneficial for future serious games.



 

Author Biographies

  • Andrew Seyderhelm, University of Newcastle

    I am into my final year of a PhD focusing on improving outcomes in simulation training; this is supported through a scholarship with the University of Newcastle and the Defence Innovation Network. In 2019 I completed a proof of concept Search Warrant Training Simulation (SWTS) for the Australian Federal Police and this work has now been formally adopted. I was previously the Serious Games & Simulation Strategist for the AFP. I am now the Future Technology Lead for an Australian Federal Government Agency, liaising with industry, academia and government, and also researching and developing XR training. In addition, I have developed course content, written lectures and lectured for University of New South Wales Masters of Visualisation, Simulation & Immersive Design. I have about 7 years experience in Investigations (Cybercrime, Serious Organised Crime and Fraud) and prior to the AFP I spent around 7 years working in the video games industry with 5 released PS2 Titles. I am currently using: Unreal, Maya, Substance, various Photogrammetry applications, Adobe products, Character creator, iClone 7 and Unity. I have run two of my own businesses and I am passionate about ways to modernise and improve training outcomes through games and simulation technologies

  • Professor Karen L. Blackmore, University of Newcastle - Professor

    Dr Karen Blackmore is a Professor, and Acting Head of School, in Computing and Information Technology at the School of Information and Physical Sciences, The University of Newcastle, Australia. She received her BIT (Spatial Science) With Distinction and PhD (2008) from Charles Sturt University, Australia. Dr Blackmore is a spatial scientist with research expertise in the modelling and simulation of complex social and environmental systems. Her research interests cover the use of agent-based models for simulation of socio-spatial interactions, and the use of simulation and games for serious purposes.  Her research is cross-disciplinary and empirical in nature, and extends to exploration of the ways that humans engage and interact with models and simulations. Before joining the University of Newcastle, Dr Blackmore was a Research Fellow in the Department of Environment and Geography at Macquarie University, Australia and a Lecturer in the School of Information Technology, Computing and Mathematics at Charles Sturt University.

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Published

2024-08-31

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How to Cite

Dynamic Adaptative Surveillance Training in a Virtual Environment Using Real-Time Cognitive Load and Performance. (2024). International Journal of Serious Games, 11(3), 109-133. https://doi.org/10.17083/ijsg.v11i3.733