Assessing the effectiveness of smart phone-based video training in invasive plant identification
Citizen science is emerging given the rapid growth and increasing popularity of smart phone technology which put sophisticated data-collection tools in the hands of more and more citizens. Jared Starr of the University of Massachusetts, Amherst, USA and colleagues argue that with smart phone apps, it is becoming increasingly practical to remotely acquire high quality citizen-submitted data at a fraction of the cost of traditional studies. Yet, one impediment to citizen science projects needs to be addressed, i.e. the question of how participants are trained because the traditional 'in-person' training model can be cost prohibitive as the spatial scale of a project increases. In the context of a study of invasive plant identification in Massachusetts, the authors explored possible solutions and analysed three training models: (i) in-person, (ii) app-based video, and (iii) app-based text/images. They found that participants who had received video training were as successful at invasive plant identification as those trained in-person. This and other findings of their study have implications for a variety of citizen science projects that need alternative methods to effectively train participants when in-person training is deemed impractical and too expensive.
(PLOS ONE, 05/11/2014)
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