City to Sea Citizen Science: Creating a Model to Engage Underrepresented Minorities in Citizen Science

In the past two decades, citizen science has been shown to be a powerful tool to build STEM literacy and decision-making skills in participants, increase the body of scientific knowledge, and inform conservation and management... [ view full abstract ]

In the past two decades, citizen science has been shown to be a powerful tool to build STEM literacy and decision-making skills in participants, increase the body of scientific knowledge, and inform conservation and management practices. Citizen science has recently become a focal point of growth for the informal science education community; however the latest literature review found little research on how these projects can specifically engage underrepresented minority groups (URMs). The participation of these groups in citizen science is currently unknown, however it has already been documented that these groups are less likely to participate in STEM broadly.

Ocean Discovery Institute is developing a community citizen science program model that targets URMs. During the first half of this study ODI developed, piloted, and enhanced a model that provides guided experiences, interactions with scientists, to increase interest in science and increase science knowledge among community participants. We piloted the model engaging 40 of middle and high school students in a study to better understand sources of trash in local canyons and pathways trash traveled through the watershed.

Surveys conducted revealed patterns related to sources of debris (stormwater versus littering) and showed the majority of debris was plastics. As well we determined how to implement our best practices and the model to provide a clear relevancy message and methods for data collection.

During the second half of the study we will be taking the model and recruiting community members to participate in the project throughout from October 2014-March 2015. They will take part in every step of the project including: data collection, data entry, data management, analysis and dissemination. We will share the innovative model, lessons learned, scientific results to date, and the challenges still underway.