This poster was presented at the 2021 NSF AISL Awardee Meeting.
Project Harvest is a co-created citizen science project that investigates the quality of household environments in Arizona communities neighboring active or legacy mining and/or toxic release. Project Harvest is a response to the community-driven questions, “Are there pollutants in harvested rainwater? Can I use the harvested rainwater for my garden?"
Millions of people around the world watch live streaming wildlife cams, but they aren’t just watching: they are asking questions, trading information, and witnessing events that may be undocumented in the scientific literature. The goal of Bird Cams Lab was to design a digital space and framework enabling online communities to engage in a co-created scientific inquiry process utilizing wildlife cams to answer bird-related questions of common interest. To achieve this goal, the project engaged participants at every stage of the research process—including observation, generating and selecting
Informal learning institutions (ILIs) create opportunities to increase public understanding of science and promote increased inclusion of groups underrepresented in Science, Technology, Engineering, and Math (STEM) careers but are not equally distributed across the United States. We explore geographic gaps in the ILI landscape and identify three groups of underserved counties based on the interaction between population density and poverty percentage. Among ILIs, National Park Service lands, biological field stations, and marine laboratories occur in areas with the fewest sites for informal
Final External Evaluation Report for Informal STEM Learning at Biological Field Stations, an NSF AISL Exploratory Pathways project, which studied the pedagogical and andragogical characteristics of informal educational outreach activities at field stations. This report summarizes the project team’s major research activities and the contextual factors that supported that work.
Appendix includes interview protocol.
Learning to See, Seeing to Learn is a National Science Foundation-funded project to develop www.macroinvertebrates.org, a digital observation tool and set of informational resources that can supplement volunteer biomonitoring trainings and improve aquatic macroinvertebrates identification. Project researchers are interested in how trainers and volunteers use the tool, as well as how training that incorporates the tool impacts volunteers’ confidence in and accuracy around aquatic macroinvertebrates identification. In November 2018, project partner, Stroud Water Research Center, conducted a
Identifying private gardens in the U.K. as key sites of environmental engagement, we look at how a longer-term online citizen science programme facilitated the development of new and personal attachments of nature. These were visible through new or renewed interest in wildlife-friendly gardening practices and attitudinal shifts in a large proportion of its participants. Qualitative and quantitative data, collected via interviews, focus groups, surveys and logging of user behaviours, revealed that cultivating a fascination with species identification was key to both ‘helping nature’ and wider
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TEAM MEMBERS:
Nirwan SharmaSam GreavesAdvaith SiddharthanHelen AndersonAnnie RobinsonLaura Colucci-GrayAgung Toto WibowoHelen BostockAndrew SalisburyStuart RobertsDavid SlawsonRené van der Wal
In citizen science, user-centred development is often emphasised for its potential to involve participants in the development of technology. We describe the development process of the mobile app “Naturblick” as an example of a user-centred design in citizen science and discuss digital user feedback with regard to the users' involvement. We have identified three types of digital user feedback using qualitative content analysis: general user feedback, contributory user feedback and co-creational user feedback. The results indicate that digital user feedback can link UCD techniques with more
The RASOR project is designed to increase engagement of students from rural Alaska communities in biomedical/STEM careers. Rural Alaskan communities are home to students of intersecting identities underrepresented in biomedical science, including Alaska Native, low-income, first generation college, and rural. Geographic isolation defines these communities and can limit the exposure of students to scientifically-minded peers, professional role models, and science career pathways. However these students also have a particularly strong environmental connection through subsistence and recreational activities, which makes the one-health approach to bio-medicine an intuitive and effective route for introducing scientific research and STEM content. In RASOR, we will implement place-based mentored research projects with students in rural Alaskan communities at the high school level, when most students are beginning to seriously consider career paths. The biomedical one-health approach will build connections between student experiences of village life in rural Alaska and biomedical research. Engaging undergraduate students in research has proved one of the most successful means of increasing the persistence of minority students in science (Kuh 2008). Furthermore, RASOR will integrate high school students into community-based participatory research (Israel et al. 2005). This approach is designed to demonstrate the practicality of scientific research, that science has the ability to support community and cultural priorities and to provide career pathways for individual community members. The one-health approach will provide continuity with BLaST, an NIH-funded BUILD program that provides undergraduate biomedical students with guidance and support. RASOR will work closely with BLaST, implementing among younger (pre-BLaST) students approaches that have been successful for retaining rural Alaska students along STEM pathways and tracking of post-RASOR students. Alaska Native and rural Alaska students are a unique and diverse population underrepresented in biomedical science and STEM fields.
A team of experts from five institutions (University of Minnesota, Adler Planetarium, University of Wyoming, Colorado State University, and UC San Diego) links field-based and online analysis capabilities to support citizen science, focusing on three research areas (cell biology, ecology, and astronomy). The project builds on Zooniverse and CitSci.org, leverages the NSF Science Gateways Community Institute, and enhances the quality of citizen science and the experience of its participants.
This project creates an integrated Citizen Science Cyberinfrastructure (CSCI) framework that expands the capacity of research communities across several disciplines to use citizen science as a suitable and sustainable research methodology. CSCI produces three improvements to the infrastructure for citizen science already provided by Zooniverse and CitSci.org:
Combining Modes - connecting the process of data collection and analysis;
Smart Assignment - improving the assignment of tasks during analysis; and
New Data Models - exploring the Data-as-Subject model. By treating time series data as data, this model removes the need to create images for classification and facilitates more complex workflows. These improvements are motivated and investigated through three distinct scientific cases:
Biomedicine (3D Morphology of Cell Nucleus). Currently, Zooniverse 'Etch-a-Cell' volunteers provide annotations of cellular components in images from high-resolution microscopy, where a single cell provides a stack containing thousands of sliced images. The Smart Task Assignment capability incorporates this information, so volunteers are not shown each image in a stack where machines or other volunteers have already evaluated some subset of data.
Ecology (Identifying Individual Animals). When monitoring wide-ranging wildlife populations, identification of individual animals is needed for robust estimates of population sizes and trends. This use case combines field collection and data analysis with deep learning to improve results.
Astronomy (Characterizing Lightcurves). Astronomical time series data reveal a variety of behaviors, such as stellar flares or planetary transits. The existing Zooniverse data model requires classification of individual images before aggregation of results and transformation back to refer to the original data. By using the Data-as-Subject model and the Smart Task Assignment capability, volunteers will be able to scan through the entire time series in a machine-aided manner to determine specific light curve characteristics.
The team explores the use of recurrent neural networks (RNNs) to determine automated learning architectures best suited to the projects. Of particular interest is how the degree to which neighboring subjects are coupled affects performance. The integration of existing tools, which is based on application programming interfaces (APIs), also facilitates further tool integration. The effort creates a citizen science framework that directly advances knowledge for three science use cases in biomedicine, ecology, and astronomy, and combines field-collected data with data analysis. This has the ability to solve key problems in the individual applications, as well as benefiting the research of the dozens of projects on the Zooniverse platform. It provides benefits to researchers using citizen scientists, and to the nearly 1.6 million citizen scientists themselves.
This award by the Office of Advanced Cyberinfrastructure is jointly supported by the Division of Research on Learning in Formal and Informal Settings, within the NSF Directorate for Education and Human Resources.
This project is funded by the National Science Foundation's (NSF's) Advancing Informal STEM Learning (AISL) program, which supports innovative research, approaches, and resources for use in a variety of learning settings.
Given the current level of Galeophobia, or fear of sharks, that’s an excellent question. Most people will leave the water immediately if they think a shark is in the area. Oddly, the greatest number of those who fear sharks seem to come from those who rarely, if ever, go into the ocean—so, clearly, this is a primal fear, much like snakes or spiders.
Enter the average scuba diver. Our experience at Ocean Sanctuaries suggests that many (but not all)divers have great respect for these apex predators and—ready for this?—Can’t wait to dive with them. They engender such awe and fear, that merely
The HOWL science team set out to analyze the quality of the Hofmann Forest’s watershed in order to understand the Hofmann’s place in the coastal ecosystem as a whole and how its quality would affect the surrounding human and ecological community. However, we realized quickly that we would need help collecting hundreds of stream water samples and observations, and so we partnered with the Izaak Walton League to help us contact and get local community members involved in such an overwhelming task. Local volunteers will not only help collect samples for this large-scale citizen science project, but will also help us try out some new equipment for water sampling and testing. And so, along with your help, the HOWL Project will:
Gain knowledge of water quality, and quantity, of the White Oak, New, and Trent Rivers in the Hofmann Forest in Eastern NC.
Demonstrate the feasibility of using low-cost analytical equipment for water quality testing.
Increase understanding of North Carolina’s rapidly changing coast due to the threats of sea-level rise, deforestation, agricultural expansion, and new substantial developments.
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TEAM MEMBERS:
Meredith HovisFrederick CubbageMadhusudan KattiKathleen McGinley
Citizen science, also known as participatory research, combines the efforts among professional researchers and community volunteers to collect data. We have established a collaborative project in eastern North Carolina, near the 79,000-acre Hofmann Forest, comprising of 55,000 acres of planted forests and 24,00 acres of deep pocosin natural forests. The White Oak River, New River, and Trent River all flow out of the Hofmann. The Hofmann acts plays a keystone ecological role as it acts as a natural filtration system for harmful runoff that occurs in the coastal plain of North Carolina.
The
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TEAM MEMBERS:
Meredith HovisFrederick CubbageMadhusudan KattiKathleen McGinley