Effects of Field of View and Visual Complexity on Virtual Reality Training Effectiveness for a Visual Scanning Task
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Cyber and Information Security Group
- Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States). Dept. of Computer Science
- Duke Univ., Durham, NC (United States)
- Precision Nutrition, Toronto, ON (Canada)
- Univ. of Texas-Dallas, Richardson, TX (United States)
Virtual reality training systems are commonly used in a variety of domains, and it is important to understand how the realism of a training simulation influences training effectiveness. We conducted a controlled experiment to test the effects of display and scenario properties on training effectiveness for a visual scanning task in a simulated urban environment. The experiment varied the levels of field of view and visual complexity during a training phase and then evaluated scanning performance with the simulator's highest levels of fidelity and scene complexity. To assess scanning performance, we measured target detection and adherence to a prescribed strategy. The results show that both field of view and visual complexity significantly affected target detection during training; higher field of view led to better performance and higher visual complexity worsened performance. Additionally, adherence to the prescribed visual scanning strategy during assessment was best when the level of visual complexity during training matched that of the assessment conditions, providing evidence that similar visual complexity was important for learning the technique. The results also demonstrate that task performance during training was not always a sufficient measure of mastery of an instructed technique. That is, if learning a prescribed strategy or skill is the goal of a training exercise, performance in a simulation may not be an appropriate indicator of effectiveness outside of training-evaluation in a more realistic setting may be necessary.
- Research Organization:
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
- Sponsoring Organization:
- USDOE; US Department of the Navy, Office of Naval Research (ONR)
- Grant/Contract Number:
- AC05-00OR22725
- OSTI ID:
- 1185475
- Alternate ID(s):
- OSTI ID: 1261446
- Journal Information:
- IEEE Transactions on Visualization and Computer Graphics, Vol. 21, Issue 7; ISSN 1077-2626
- Publisher:
- IEEECopyright Statement
- Country of Publication:
- United States
- Language:
- English
Web of Science
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