• Media type: E-Article
  • Title: Human-Computer Interaction – INTERACT 2021: Stress Out: Translating Real-World Stressors into Audio-Visual Stress Cues in VR for Police Training
  • Contributor: Nguyen, Quynh; Jaspaert, Emma; Murtinger, Markus; Schrom-Feiertag, Helmut; Egger-Lampl, Sebastian; Tscheligi, Manfred
  • Published: Springer International Publishing, 2021
  • Published in: Human-Computer Interaction – INTERACT 2021 (2021), Seite 551-561
  • Language: Not determined
  • DOI: 10.1007/978-3-030-85616-8_32
  • ISBN: 9783030856151; 9783030856168
  • ISSN: 0302-9743; 1611-3349
  • Origination:
  • Footnote:
  • Description: AbstractVirtual Reality (VR) training has become increasingly important for police first responders in recent years. Improving the training experience in such complex contexts requires ecological validity of virtual training. To achieve this, VR systems need to be capable of simulating the complex experiences of police officers ‘in the field.’ One way to do this is to add stressors into training simulations to induce stress similar to the stress experienced in real-life situations, particularly in situations where this is difficult (e.g., dangerous or resource-intensive) to achieve with traditional training. To include stressors in VR, this paper thus presents the concept of so-called ‘stress cues’ for operationalizing stressors to augment training in VR simulations for the context of police work. Considering the level of complexity of police work and training, a co-creation process that allows for creative collaboration and mitigation of power imbalances was chosen to access the police officers’ knowledge and experience. We assert that stress cues can improve the training experience from the trainer’s perspective as they provide novel interaction design possibilities for trainers to control the training experience. E.g., by actively intervening in training and dynamically changing the interaction space for trainees which also improves the trainee’s experience. Stress cues can also improve the trainee’s experience by enabling personalizable and customizable training based on real-time stress measurements and supplementing information for improved training feedback.