Computer Science – Graphics
Scientific paper
Jan 2011
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2011aas...21715814b&link_type=abstract
American Astronomical Society, AAS Meeting #217, #158.14; Bulletin of the American Astronomical Society, Vol. 43, 2011
Computer Science
Graphics
Scientific paper
Moon Zoo is an online citizen science project with the aim of providing detailed crater counts for as much of the Moon's surface as possible. In addition to focusing on craters, volunteers are encouraged to remain vigilant for sightings of atypical features which may lead to new discoveries. Volunteers accomplish these tasks by exploring images captured by NASA's Lunar Reconnaissance Orbiter (LRO) which has a resolution of 50cm per pixel. To be successful, Moon Zoo needs to attract and retain a large population of citizen scientists. In this study, we examine the factors motivating Moon Zoo participants who invest many hours exploring these images.
In this, the first of a two-phased study, we conducted a qualitative analysis using semi-structured interviews as a means of data collection. A stratified sample of participants was used in an attempt to uncover the driving forces behind decisions to participate from a wide-range of participants. Inquiring and probing questions were asked about factors which led volunteers to Moon Zoo as well as reasons which kept them committed to exploring the Moon's surface through this online portal. Responses were then categorized using a grounded theory approach, and frequency distributions are calculated where appropriate.
Aggregate results from these interviews are presented here including the demographics of the sample and motivators as per the content analysis. The information gathered from this phase will be used to guide the development of an online survey to further explore volunteers’ motivation based on the presented classification schemes. The survey will then be used to guide future research and development in the area of citizen science in the field of astronomy. These findings will also be useful in charting new boundaries for future research.
Brown Shanique
Daus C. S.
Gay Pamela L.
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