Advertisement

Communicating Meaning and Role in Distributed Design Collaboration: How Crowdsourced Users Help Inform the Design of Telepresence Robotics

  • David Sirkin
  • Wendy Ju
  • Mark Cutkosky
Chapter
Part of the Understanding Innovation book series (UNDINNO)

Abstract

Design has been described as a conversation: with the problem that is being addressed, with materials and artifacts, with our colleagues and ourselves. The language of this conversation is made up of words and images, actions and behaviors. Focusing on the role of gesture in design collaboration, we ran two studies to explore how embodied telepresence robots, or physical avatars, can support better communication in distributed teams. The studies drew upon crowdsourced study participants to provide their impressions of: (1) the meaning of individual gestures, and (2) the social roles of design team partners. Distant collaborators were better understood when their telepresence intermediaries portrayed relevant gestures in concert with their facial expressions. When the avatars displayed such physical motions, teammates on both sides of the interaction were perceived as more involved in the conversation, more composed in demeanor, and more equal in stature. Our next step is to apply these requirements to the design of our next generation of field-robust communication avatar.

Keywords

Facial Expression Local Teammate Local Participant Physical Avatar Remote Collaborator 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

The authors would like to thank the Hasso Plattner Institute—Stanford Design Thinking Research Program for funding this project; Professors Mark Cutkosky and Larry Leifer for supervising the research; and collaborators Eric Kent for co-designing and constructing robot avatars and contributing to the content of the studies; Rebecca Currano for contributing to the content of the video prototypes and studies; and Samson Phan for guiding the design and safety of our robot avatars.

References

  1. 1.
    Hall, E. (1959) The silent language. Garden City, NY: Doubleday.Google Scholar
  2. 2.
    Argyle, M. (1988) Bodily communication. London, England: Methuen.Google Scholar
  3. 3.
    Sirkin, D. (2010) Physicality in distributed design collaboration: How embodiment and gesture can re-establish rapport and support better design. In H. Plattner, C. Meinel and L. Leifer (Eds.) Design thinking: Understand, improve, apply, 165–178. Berlin, Germany: Springer.Google Scholar
  4. 4.
    Clark, H. (2003) Pointing and placing. In S. Kita (Ed.) Pointing: Where language, culture and cognition meet, 243–268. Hillsdale, NJ: Erlbaum.Google Scholar
  5. 5.
    Howe, J. (2006) The rise of crowdsourcing. Wired Magazine 14(6).Google Scholar
  6. 6.
    Kittur, A. and Kraut, R. (2008) Harnessing the wisdom of crowds in Wikipedia: Quality through coordination. Proceedings of the 26 th Annual SIGCHI Conference on Human Factors in Computing Systems, ACM Press, 37–46.Google Scholar
  7. 7.
    Ross, J., Irani, L., Silberman, M., Zaldivar, A. and Tomlinson, B. (2010) Who are the crowdworkers?: Shifting demographics in Mechanical Turk. Extended Abstracts of the 28 th Annual SIGCHI Conference on Human Factors in Computing Systems, ACM Press, 2863–2872.Google Scholar
  8. 8.
    Kittur, A., Chi, E. and Suh, B. (2008) Crowdsourcing user studies with Mechanical Turk. Proceedings of the 26 th Annual SIGCHI Conference on Human Factors in Computing Systems, ACM Press, 453–456.Google Scholar
  9. 9.
    Dow, S., Glassco, A., Kass, J., Schwarz, M., Schwartz, D. and Klemmer, S. (2010) Parallel prototyping leads to better design results, more divergence, and increased self-efficacy. In ACM Transactions on Computer-Human Interaction 17(4), ACM Press, 1–24.Google Scholar
  10. 10.
    Feng, D., Besana, S. and Zajac, R. (2009) Acquiring high quality non-expert knowledge from on-demand workforce. Proceedings on the 2009 Workshop on the People’s Web Meets NLP, ACL and AFNLP, 51–56.Google Scholar
  11. 11.
    Downs, J., Holbrook, M., Sheng, S. and Cranor, L. (2010) Are your participants gaming the system? Proceedings of the 28 th Annual SIGCHI Conference on Human Factors in Computing Systems, ACM Press, 2399–2402.Google Scholar
  12. 12.
    Gaver, B., Dunne, T. and Pacenti, E. (1999) Design: Cultural probes. Interactions 6(1), 21–29.CrossRefGoogle Scholar
  13. 13.
    Ju, W. and Takayama, L. (2009) Approachability: How people interpret automatic door movement as gesture. International Journal of Design 3(2), 77–86.Google Scholar
  14. 14.
    Kidd, C. (2003) Sociable robots: The role of presence and task in human robot interaction. Master’s Thesis, MIT.Google Scholar
  15. 15.
    Woods, S., Walters, M., Koay, K. and Dautenhahn, K. (2006) Methodological issues in HRI: A comparison of live and video-based methods in robot to human approach and direction trials. Proceedings of the 15 th IEEE International Symposium on Robot and Human Interactive Communication, IEEE Press, 51–58.Google Scholar
  16. 16.
    Dillard, J., Solomon, D. and Palmer, M. Structuring the concept of relational communication. Communication Monographs 66, 49–65.Google Scholar
  17. 17.
    Coan, J. and Gottman, J. (2007) The specific affect (SPAFF) coding system. In J. Coan and J. Allen (Eds.) Handbook of emotion elicitation and assessment, 106–123. New York, NY: Oxford University Press.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Center for Design ResearchStanford UniversityStanfordUSA

Personalised recommendations