ENGAGEMENT AND LEARNING IN ENVIRONMENTALLY-BASED CITIZEN SCIENCE: A MIXED METHODS COMPARATIVE CASE STUDY

Citizen science has existed for centuries, but in its modern form is broadly defined as the intentional engagement of the public in scientific research. The potential for achieving learning outcomes in citizen science is great, but there is a need to first understand what those potential learning outcomes are and how they have been studied within the field. Further, engagement in citizen science can take many forms and it is argued that deeper engagement with the science process yields deeper learning outcomes. However, few studies have examined engagement deeply and fewer still across multiple projects. The ways in which people engage in citizen science and how their engagement relates to learning, is largely unknown. Using a mixed methods comparative case study approach, this research first describes an empirically derived conceptual model for articulating learning outcomes within citizen science that includes the following constructs: interest in science and the environment; efficacy for learning/doing science and environmental action; motivation for learning/doing science and environmental action; understanding of the Nature of Science; skills related to science inquiry; and environmental stewardship. Next, five dimensions of engagement—motivation, behavioral, cognitive, affective and social—are explored qualitatively through interviews with 72 citizen science participants from six different projects. Lastly, using data from an online survey with more than 1,500 respondents from the same six projects, the dimensions of engagement are quantified and analyzed for their association with three learning outcomes: self-efficacy, skills of science inquiry, and environmental stewardship. Triangulation of datasets reveal that participants in co-created projects are more likely to be driven by extrinsic motivations than participants in contributory projects. Aggregated across the dataset, the three most common project activities include: gathering data, submitting data, and sharing information about the project with others. Quantitative data analysis reveals that higher levels of reported behavioral engagement has a positive, statistically significant relationship with self-perceived skills of science inquiry. Other positive statistically significant associations were detected, but the strength of the relationships varied across projects, project types, and project structures. This work lends empirical evidence for theorizing about the nature of learning and engagement in citizen science