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Abstract

Virtual environments can support psychomotor learning by allowing learners to observe instructor avatars. Instructor avatars that look like the learner hold promise in enhancing learning; however, it is unclear whether this works for psychomotor tasks and how similar avatars need to be. We investigated ‘minimal’ customisation of instructor avatars, approximating a learner’s appearance by matching only key visual features: gender, skin-tone, and hair colour. These avatars can be created easily and avoid problems of highly similar avatars. Using modern dancing as a skill to learn, we compared the effects of visually similar and dissimilar avatars, considering both learning on a screen (n=59) and in VR (n=38). Our results indicate that minimal avatar customisation leads to significantly more vivid visual imagery of the dance moves than dissimilar avatars. We analyse variables affecting interindividual differences, discuss the results in relation to theory, and derive design implications for psychomotor training in virtual environments.
Original languageEnglish
Title of host publicationCHI 2023 - Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems
Subtitle of host publicationProceedings of the 2023 CHI Conference on Human Factors in Computing Systems
Place of PublicationNew York, U. S. A.
PublisherAssociation for Computing Machinery
Number of pages16
ISBN (Electronic)9781450394215
DOIs
Publication statusPublished - 19 Apr 2023
Event2023 CHI Conference on Human Factors in Computing Systems, CHI 2023 - Hamburg, Germany
Duration: 23 Apr 202328 Apr 2023

Publication series

NameConference on Human Factors in Computing Systems - Proceedings

Conference

Conference2023 CHI Conference on Human Factors in Computing Systems, CHI 2023
Country/TerritoryGermany
CityHamburg
Period23/04/2328/04/23

Bibliographical note

Isabel Fitton’s research is funded by the UKRI EPSRC Centre for
Doctoral Training in Digital Entertainment (CDE), EP/L016540/1
and industrial partner PwC. This work was also supported and
partly funded by the Centre for the Analysis of Motion, Entertainment Research and Applications (CAMERA 2.0; EP/T022523/1) at the University of Bath

Keywords

  • Avatar Customisation
  • Psychomotor
  • Skills Training
  • Virtual Environments
  • Virtual Reality

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design

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