Identifying learning dimensions in citizen science projects

Abstract

Citizen Science (CS) is attracting increasing interest and attention from multiple sectors of society. Educational impacts of participation, such as the development of scientific skills or increased awareness about biodiversity and conservation, are one of the most widely discussed aspects of CS. Whereas most existing studies investigate perceived or observed learning gains of citizen scientists, this paper takes an alternative perspective by examining learning-related aspects in textual self-representations of CS projects - namely project descriptions posted online. Project descriptions were chosen as objects of analysis both because they can easily be accessed and collected through automated web crawling, and because, as key elements of a CS project’s online presence, they play an important role in recruiting volunteers. We have thus conducted a qualitative content analysis of 94 project descriptions with the goal of examining what they tell us about learning dimensions associated with participation in these CS projects. Building on the model of individual learning outcomes developed by Phillips et al. in 2018 [1] as a theoretical framework, our analysis shows that some learning dimensions (such as data collection or using technology), are very prominently discussed in the project descriptions we studied, while others (e.g. experimenting, study design, community action) are clearly underrepresented. In other words, the project descriptions analyzed only partially reflect the educational potential of participation in CS. In the discussion section of this paper, we suggest possible explanations and ways in which this issue could be addressed on the level of both project design and project communication.