Being present in online communities: Learning in citizen science

Gabriel Mugar, Corey Brian Jackson, Carsten Østerlund, Kevin Crowston

Research output: Chapter in Book/Entry/PoemChapter (peer-reviewed)peer-review

11 Scopus citations


How online community members learn to become valuable contributors constitutes a long-standing concern of Community & Technology researchers. The literature tends to highlight participants' acceb to practice, feedback from experienced members, and relationship building. However, not all crowdsourcing environments offer participants opportunities for acceb, feedback, and relationship building (e.g., Citizen Science). We study how volunteers learn to participate in a citizen science project, Planet Hunters, through participant observation, interviews, and trace ethnography. Drawing on Sørensen's sociomaterial theories of presence, we extend the notion of situated learning to include several modes of learning. The empirical findings suggest that volunteers in citizen science engage more than one form of acceb to practice, feedback, and relationship building. Communal relations characterize only one form of learning. Equally important to their learning are authority-subject and agent-centered forms of acceb, feedback, and relationship building.

Original languageEnglish (US)
Title of host publicationProceedings of the International Conference on Communities and Technologies
EditorsFiorella de Cindio, Gabriela Avram, Volkmar Pipek
PublisherAssociation for Computing Machinery
Number of pages10
ISBN (Electronic)9781450334600
StatePublished - Jun 27 2015
Event7th International Conference on Communities and Technologies, C and T 2015 - Limerick, Ireland
Duration: Jun 27 2015Jun 30 2015

Publication series

NameACM International Conference Proceeding Series


Other7th International Conference on Communities and Technologies, C and T 2015


  • Citizen science
  • Situated learning
  • Sociomateriality

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications


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