Same Task, Different Place: Developing Novel Simulation Environments with Equivalent Task Difficulties
- 655 Downloads
We introduce a novel framework for creating and evaluating multiple virtual reality environments (VEs) that are naturalistic and similar in navigational complexity. We developed this framework in support of a spatial-learning study using a within-subjects design. We generated three interior environments and used graph-theoretic methods to ensure similar complexity. We then developed a scavenger-hunt task that ensured participants would visit all parts of the environments. Here, we describe VE development and a user study evaluating the relative task difficulty in the environments. Our results showed that our techniques were generally successful: the average time to complete the task was similar across environments. Some participants took longer to complete the task in one of the environments, indicating room for refinement of our framework. The methods described here should be of use for future studies using VEs, especially in within-subjects design.
KeywordsVirtual environments Graph-theoretic measures Within-subjects designs Task development Floorplan design Bayesian modelling
This work was funded by the US Army Research Laboratory’s Human sciences campaign. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Laboratory or U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation herein. The authors thank Debbie Patton, Mark Ericson, and the entire Training Effectiveness/Immersion group for their comments and suggestions on this work. Bianca Dalangin helped conduct the user study.
- 4.Zimmons, P., Panter, A.: The influence of rendering quality on presence and task performance in a virtual environment. In: Proceedings of IEEE Virtual Reality 2003, pp. 293–294 (2003)Google Scholar
- 5.Steadman, P.: Graph theoretic representation of architectural arrangement. Archit. Res. Teach. 2, 161–172 (1973)Google Scholar
- 7.Levy, R.M., O’Brien, M.G., Aorich, A.: Prediciting the behavior of game players - space syntax and urban planning theory as a predictive tool in game design. In: 2009 15th International Conference on Virtual Systems and Multimedia, pp. 203–208 (2009)Google Scholar
- 9.Sinatra, A.M., et al.: Development of cognitive transfer tasks for virtual environments and applications for adaptive instructional systems. In: Lecture Notes in Computer Science. Springer, Orlando (2019, forthcoming)Google Scholar
- 10.Carpenter, B., et al.: Stan : a probabilistic programming language. J. Stat. Softw. 76, 1–32 (2017)Google Scholar
- 11.Stan Development Team: RStan: the R interface to Stan (2018)Google Scholar