Biases influence the decisions people make in everyday life, even if they are unaware of it. The current study investigates the extent bias behavior transfers into social interactions in virtual worlds by investigating the effect of aversive racism on helping behaviors and learning within a virtual world for medical triage training. In a 2 × 2 × 2 mixed design, two between subjects variables, participant skin tone (light, dark) and avatar skin tone (light, dark), and one within subjects variable, agent skin tone (light, dark), were manipulated. Effects on helping behaviors were observed on three measures: time to initiate help, errors made while helping virtual patients, and learning. Participants, regardless of their skin tone or their avatar’s skin tone, took more time to initiate help and made more errors while triaging dark-skinned agents in comparison to light-skinned agents. The bias against virtual patients with a darker skin tone also served as a mediating factor for learning with lower prior knowledge increasing the errors made for dark skinned virtual patients, which had more of a negative impact on learning than the errors made on light skin virtual patients. This study showed that participants applied general biases against dark-skinned agents regardless of participant’s ethnicity or avatar’s skin-tone. It indicates the importance of considering biases when designing training systems.
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This research was partially supported by the Department of Defense [U.S. Army Medical Research Acquisition Activity] under Award Number (W81XWH-11-2-0171). Views and opinions of, and endorsements by the author(s) do not reflect those of the US Army or the Department of Defense. This research was also partially funded by the Fulton Undergraduate Research Initiative at Arizona State University (https://furi.engineering.asu.edu/).
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Zipp, S.A., Craig, S.D. The impact of a user’s biases on interactions with virtual humans and learning during virtual emergency management training. Education Tech Research Dev 67, 1385–1404 (2019). https://doi.org/10.1007/s11423-019-09647-6
- Aversive racism
- Virtual humans
- Animated agents
- Virtual worlds
- Virtual environments
- Emergency response training