Biological Conservation · 2020 · 120 citations · 60 references
Public AffairsConservation BiologyCommunity EngagementCommunity-based Participatory ResearchConservation ScienceCitizen EngagementCitizen ScienceCitizen Science ParticipationCivic EngagementCivic ParticipationVolunteer EngagementBarriers To Volunteer ParticipationCitizen Science Data CollectionConservation VolunteerismData Collection ParticipationOnline Social InteractionOpen-ended Interview QuestionsVolunteer Motivation Across Demographic GroupsVolunteer Rewards
Participation in conservation citizen science projects is growing rapidly and approaches to project design are diversifying. There has been a recent shift towards projects characterised by contributors collecting data in isolation and submitting findings online, with little training or opportunities for direct social interaction with other citizen scientists. While research is emerging on developing citizen science projects by optimising technological modalities, little consideration has been given to understanding what motivates individuals to voluntarily contribute data. Here, we use the Volunteer Functions Inventory, combined with open-ended questions, to demonstrate that the two strongest motivations underpinning participation, for both individuals who contribute data systematically (regularly; n = 177) and opportunistically (ad hoc basis; n = 218), are ‘Values’ and ‘Understanding’. People take part in such projects because they have an intrinsic value for the environment and want to support research efforts (representing ‘Values’), as well as wanting to learn and gain knowledge (signifying ‘Understanding’). Unlike more traditional citizen science projects that involve specific training and considerable time investments, contributors to these newer types of project are not motivated by the potential to develop their career or opportunities for social interaction. The person-level characteristics of contributors considered in this study did not reliably forecast levels of motivation, suggesting that predicting high levels of motivation is inherently more complex than is often speculated. We recommend avenues for future research that may further enhance our understanding of contributor motivations and the characteristics that may underpin levels of motivation.
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Virginia Braun, Victoria Clarke · Qualitative Research in Psychology · 2006 · 183.3K citations · Full text
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