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SUMMARY:Motivation and learning in citizen science: The role of automatica
 lly generated feedback. - Advaith Siddharthan\, University of Aberdeen
DTSTART:20151113T120000Z
DTEND:20151113T130000Z
UID:TALK60718@talks.cam.ac.uk
CONTACT:Tamara Polajnar
DESCRIPTION:The rapid rise of citizen science is seen as a solution to the
  mismatch between data demand and supply whilst simultaneously engaging ci
 tizens with scientific topics. In the environmental domain for example\, l
 ay people form often extensive biodiversity sensor networks. However\, suc
 h recording schemes require careful consideration of how to motivate\, tra
 in and retain volunteers\, especially where schemes concern species groups
  for which knowledge levels in society are low. The typical lack of resour
 ces within citizen science programmes for engaging with volunteers thus pr
 esents a substantial bottleneck. \n\nIn this context we evaluated the role
  of automated textual feedback aimed at improving volunteer’s species id
 entification skills and enhancing volunteer experience and retention. The 
 NLG component used a species identification key and data collected from wi
 thin a focal citizen science program to contextualize a submitted record\,
  explain reasons for any misidentification and highlight key features that
  facilitate correct identification. \n\nExperimental trials showed increas
 ed species identification accuracy and enhanced retention of participants 
 who were provided with such in-depth automated feedback\, compared to thos
 e who only received the correct identification without explanation. This f
 eedback component is now incorporated into BeeWatch\, a citizen science pr
 ogram focused on bumblebee species in the UK.
LOCATION:FW26\, Computer Laboratory
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