05 22 rotman_preece

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05 22 rotman_preece

  1. 1. Will You Help Me With This? Motivating Volunteers to Participate in Citizen Science Projects Dana Rotman, Jennifer Preece, Jennifer Hammock, Derek Hansen, Cynthia Parr, David Jacobs HCIL Symposium, May 22, 2012
  2. 2. Plymouth State University
  3. 3. Research Questions What are the major motivational factors affecting volunteers and scientists’ engagement in citizen science projects? 1 What are the major motivational barriers to such collaboration? 2
  4. 4. Principles of social participation Liam Q @ Flickr Batson, Ahmed and Chang, 2002 yarotman AP Buckeye98 @Flickr XXTeresaXX@Flickr Egoism PrincipalismCollectivism Altruism EOL AP
  5. 5. Methods Participants Scientists n = 62 (44%) Volunteers n = 80 (56%) Experience Less than a year Scientists Volunteers n = 16 n = 35 (25%) (44%) More than a year Scientists Volunteers n = 46 n = 45 (75%) (56%) Gender Male Scientists Volunteers n = 38 n = 46 (60%) (57%) Female Scientists Volunteers n = 24 n = 34 (40%) (43%) N = 142 Magnusfrankkun @ Flickr Survey 18 interviews
  6. 6. 0 1 2 3 4 5 Altruism Collectivism Principalism Egoism Motivationallevel-Likertscale Motivational Factors Scientists Volunteers N = 142
  7. 7. Scientists Education and outreach “I don’t think people can make good decisions, be it policy or environmental or anything else, unless they understand how things work. This provides the opportunity to educate people through a valid citizen science program” Data needs “I see [volunteers] as most helpful in making accurate observations… they are basically the field component”
  8. 8. Volunteers Primary motivation – personal interest “I think personal interest comes first. Personal interest and personal gain”. “I would be less inclined to participate in something I had little interest in, even if it was a worthy endeavor”
  9. 9. Secondary motivations – recognition and attribution “I’m not really, obviously, objected to glory. I do expect attribution… I would always like to be the first one to put a photo up there, it’s got to count somehow” “It’s not about spending time or money. It’s more about the constant feedback to the volunteers that what we’re doing is useful and being used” Volunteers
  10. 10. Volunteers “It’s the combination of being an affective citizen scientist and seeing the community thrive… people really care about their natural resources here” “It’s a perfect opportunity to help people understand their environment. I hope that something that you say will make a dent and make them more curious and they’ll go home and pick a book or they’ll call you back” Secondary motivations – community involvement and advocacy
  11. 11. De-motivating factors “Scientists are intimidating” “Scientists speak a different jargon” Volunteers Scientists “they may potentially contaminate the data” “we need quality control!” “people won’t come back if there isn’t a loop of credibility and trust and things that they can see that are being accomplished as a result of the data they are collecting”
  12. 12. Process model of scientists’ and volunteers’ collaboration Without scientists’ recognition = loss of motivation Personal interest initial or ongoing Initial involvement Interaction with scientists Recognition Training, attribution, feedback Continued involvement Ongoing attribution, inclusion in scientific work, community involvement , advocacy egoism egoism Egoism, collectivism, altruism Without scientists’ continued recognition = loss of motivation Scientists’ need for data Scientists’ altruistic support for public education
  13. 13. Design to support motivation  Timing is everything (egoism)  Highlight data use and reuse (Egoism) Emphasize locality (collectivism) Break tasks to small, building blocks (Collectivism & altruism) Support synergy (Collectivism)  Match scientists, volunteers and tasks (Egoism, collectivism, altruism)
  14. 14. Timing is everything toniVC @ Flickr
  15. 15. Highlighting data use and reuse http://www.divematrix.com/showthread.php?9520-hehehehe-Hermit-Crab-movin-on-up!
  16. 16. Emphasize locality toniVC @ Flickr Yarotman
  17. 17. Break tasks into smaller building blocks; support synergy Ksgr @ Flickr
  18. 18. Match scientists, volunteers and tasks muhawi001@ FlickrJessi.bryan @ Flickr
  19. 19. Conclusion Scientific projects are becoming collaborative efforts1 2 To design successful tools we need to be familiar with the various populations that participate in scientific collaborative projects 3 Collaborative scientific project are continuous – motivations change throughout the projects. Design should accord these changes
  20. 20. danarotman drotman@umd.edu Supported by NSF SoCS grant # 0968546 Questions?
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