TY - GEN
T1 - CrowDXR - Pitfalls and potentials of experiments with remote participants
AU - Zhao, Jiayan
AU - Simpson, Mark
AU - Sajjadi, Pejman
AU - Wallgrün, Jan Oliver
AU - Li, Ping
AU - Bagher, Mahda M.
AU - Oprean, Danielle
AU - Padilla, Lace
AU - Klippel, Alexander
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - Although the COVID-19 pandemic has made the need for remote data collection more apparent than ever, progress has been slow in the virtual reality (VR) research community, and little is known about the quality of the data acquired from crowdsourced participants who own a head-mounted display (HMD), which we call crowdXR. To investigate this problem, we report on a VR spatial cognition experiment that was conducted both in-lab and out-of-lab. The in-lab study was administered as a traditional experiment with undergraduate students and dedicated VR equipment. The out-of-lab study was carried out remotely by recruiting HMD owners from VR-related research mailing lists, VR subreddits in Reddit, and crowdsourcing platforms. Demographic comparisons show that our out-of-lab sample was older, included more males, and had a higher sense of direction than our in-lab sample. The results of the involved spatial memory tasks indicate that the reliability of the data from out-of-lab participants was as good as or better than their in-lab counterparts. Additionally, the data for testing our research hypotheses were comparable between in- and out-of-lab studies. We conclude that crowdsourcing is a feasible and effective alternative to the use of university participant pools for collecting survey and performance data for VR research, despite potential design issues that may affect the generalizability of study results. We discuss the implications and future directions of running VR studies outside the laboratory and provide a set of practical recommendations.
AB - Although the COVID-19 pandemic has made the need for remote data collection more apparent than ever, progress has been slow in the virtual reality (VR) research community, and little is known about the quality of the data acquired from crowdsourced participants who own a head-mounted display (HMD), which we call crowdXR. To investigate this problem, we report on a VR spatial cognition experiment that was conducted both in-lab and out-of-lab. The in-lab study was administered as a traditional experiment with undergraduate students and dedicated VR equipment. The out-of-lab study was carried out remotely by recruiting HMD owners from VR-related research mailing lists, VR subreddits in Reddit, and crowdsourcing platforms. Demographic comparisons show that our out-of-lab sample was older, included more males, and had a higher sense of direction than our in-lab sample. The results of the involved spatial memory tasks indicate that the reliability of the data from out-of-lab participants was as good as or better than their in-lab counterparts. Additionally, the data for testing our research hypotheses were comparable between in- and out-of-lab studies. We conclude that crowdsourcing is a feasible and effective alternative to the use of university participant pools for collecting survey and performance data for VR research, despite potential design issues that may affect the generalizability of study results. We discuss the implications and future directions of running VR studies outside the laboratory and provide a set of practical recommendations.
KW - Crowdsourcing
KW - Remote experiments
KW - Spatial cognition
KW - Virtual reality
UR - http://www.scopus.com/inward/record.url?scp=85126395741&partnerID=8YFLogxK
U2 - 10.1109/ISMAR52148.2021.00062
DO - 10.1109/ISMAR52148.2021.00062
M3 - Conference article published in proceeding or book
AN - SCOPUS:85126395741
T3 - Proceedings - 2021 IEEE International Symposium on Mixed and Augmented Reality, ISMAR 2021
SP - 450
EP - 459
BT - Proceedings - 2021 IEEE International Symposium on Mixed and Augmented Reality, ISMAR 2021
A2 - Marchal, Maud
A2 - Ventura, Jonathan
A2 - Olivier, Anne-Helene
A2 - Wang, Lili
A2 - Radkowski, Rafael
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 20th IEEE International Symposium on Mixed and Augmented Reality, ISMAR 2021
Y2 - 4 October 2021 through 8 October 2021
ER -