The Sense of Presence between Volumetric-Video and Avatar-Based Augmented Reality and Physical-Zoom Teaching Activities

Xuanru Guo, Takashi Yoshinaga, Aaron Hilton, Shuji Harumoto, Ema Hilton, Shizuka Ono, Takeharu Seno

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Various types of Augmented Reality (AR) have been successfully applied to many highly operable and spatial teaching courses in medicine, chemistry, and others. AR has already shown advantages over traditional face-to-face and online teaching, such as Zoom or Teams meetings. However, it is unclear when comparing teaching activity whether new AR technologies can offer similar advantages disciplines that are non-highly operational or non-spatial in nature, such as Introduction to Psychology. In order to present teaching activities in three dimensions and all directions and realize the presence of a teacher’s face movement, we developed two new methods: Volumetric video Augmented Reality (VAR) and Avatar-based Augmented Reality (AAR). We compared the effects of teaching psychology using four methods: VAR, AAR, face-to-face, and Zoom. The par ticipants’ data were collected via questionnaires with which we conducted variance analysis and Pearson correlation analysis. Our experiments showed that there were no significant differences in the effects of teaching under the four different teaching methods, but the AAR and VAR groups had significantly higher curriculum novelty and satisfaction, 3D sensation and presence, and teacher’s attractiveness than face-to-face and Zoom groups. The research demonstrated that both VAR and AAR can improve the sense of presence and satisfaction in teaching psychology-related courses.

Original languageEnglish
Pages (from-to)267-280
Number of pages14
JournalPresence: Teleoperators and Virtual Environments
Volume28
DOIs
Publication statusPublished - May 13 2022

All Science Journal Classification (ASJC) codes

  • Software
  • Control and Systems Engineering
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition

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