TY - GEN
T1 - Measuring and Comparing Collaborative Visualization Behaviors in Desktop and Augmented Reality Environments
AU - Kintscher, Michael
AU - Huang, Jinbin
AU - Arunkumar, Anjana
AU - Amresh, Ashish
AU - Bryan, Chris
N1 - Publisher Copyright:
© 2023 ACM.
PY - 2023/10/9
Y1 - 2023/10/9
N2 - Augmented reality (AR) provides a significant opportunity to improve collaboration between co-located team members jointly analyzing data visualizations, but existing rigorous studies are lacking. We present a novel method for qualitatively encoding the positions of co-located users collaborating with head-mounted displays (HMDs) to assist in reliably analyzing collaboration styles and behaviors. We then perform a user study on the collaborative behaviors of multiple, co-located synchronously collaborating users in AR to demonstrate this method in practice and contribute to the shortfall of such studies in the existing literature. Pairs of users performed analysis tasks on several data visualizations using both AR and traditional desktop displays. To provide a robust evaluation, we collected several types of data, including software logging of participant positioning, qualitative analysis of video recordings of participant sessions, and pre- and post-study questionnaires including the NASA TLX survey. Our results suggest that the independent viewports of AR headsets reduce the need to verbally communicate about navigating around the visualization and encourage face-to-face and non-verbal communication. Our novel positional encoding method also revealed the overlap of task and communication spaces vary based on the needs of the collaborators.
AB - Augmented reality (AR) provides a significant opportunity to improve collaboration between co-located team members jointly analyzing data visualizations, but existing rigorous studies are lacking. We present a novel method for qualitatively encoding the positions of co-located users collaborating with head-mounted displays (HMDs) to assist in reliably analyzing collaboration styles and behaviors. We then perform a user study on the collaborative behaviors of multiple, co-located synchronously collaborating users in AR to demonstrate this method in practice and contribute to the shortfall of such studies in the existing literature. Pairs of users performed analysis tasks on several data visualizations using both AR and traditional desktop displays. To provide a robust evaluation, we collected several types of data, including software logging of participant positioning, qualitative analysis of video recordings of participant sessions, and pre- and post-study questionnaires including the NASA TLX survey. Our results suggest that the independent viewports of AR headsets reduce the need to verbally communicate about navigating around the visualization and encourage face-to-face and non-verbal communication. Our novel positional encoding method also revealed the overlap of task and communication spaces vary based on the needs of the collaborators.
KW - Augmented reality
KW - Co-located collaboration
KW - Visualization
UR - http://www.scopus.com/inward/record.url?scp=85175238075&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85175238075&partnerID=8YFLogxK
U2 - 10.1145/3611659.3615691
DO - 10.1145/3611659.3615691
M3 - Conference contribution
AN - SCOPUS:85175238075
T3 - Proceedings of the ACM Symposium on Virtual Reality Software and Technology, VRST
BT - VRST 2023 - 29th ACM Symposium on Virtual Reality Software and Technology
PB - Association for Computing Machinery
T2 - 29th ACM Symposium on Virtual Reality Software and Technology, VRST 2023
Y2 - 9 October 2023 through 11 October 2023
ER -