By engaging diverse publics in immersive and deliberative learning forums, this three-year project will use NOAA data and expertise to strengthen community resilience and decision-making around a variety of climate and weather-related hazards across the United States. Led by Arizona State University’s Consortium for Science, Policy & Outcomes and the Museum of Science Boston, the project will develop citizen forums hosted by regional science centers to create a new, replicable model for learning and engagement. These forums, to be hosted initially in Boston and Phoenix and then expanded to an additional six sites around the U.S., will facilitate public deliberation on real-world issues of concern to local communities, including rising sea levels, extreme precipitation, heat waves, and drought. The forums will identify and clarify citizen values and perspectives while creating stakeholder networks in support of local resilience measures. The forum materials developed in collaboration with NOAA will foster better understanding of environmental changes and best practices for improving community resiliency, and will create a suite of materials and case studies adaptable for use by science centers, teachers, and students. With regional science centers bringing together the public, scientific experts, and local officials, the project will create resilience-centered partnerships and a framework for learning and engagement that can be replicated nationwide.
Children in the Norfolk, Va., area will inherit the second highest sea level rise on the East Coast. In response, the non-profit Elizabeth River Project will prepare one of the first comprehensive youth education programs on climate change resilience on this coast. The Elizabeth River Project, working since 1993 to restore the environmental health of the urban Elizabeth River, will deploy its Dominion Virginia Power Learning Barge, “America’s Greenest Vessel,” and its new urban park, Paradise Creek Nature Park, to empower 21,000 K-12 students over three years to become informed decision makers and environmental stewards, prepared to adapt to rising seas. The project primarily will reach under-served schools in Norfolk and adjoining Portsmouth, Va. Lead science partner will be Old Dominion University, on the forefront of climate change research. Other partners include the Chrysler Museum of Art, ground zero for street flooding that has become routine in Norfolk. A youth strategy for the Elizabeth River “watershed” or drainage area will be disseminated nationally internationally by the City of Norfolk through its participation as one the Rockefeller Foundation’s 100 Resilient Cities. The youth strategy will be used by Norfolk to complement its Norfolk Resilience Strategy, prepared so far with adults in mind.
The Maritime Aquarium at Norwalk is located at the mouth of the Norwalk River where it flows into Long Island Sound. Its mission is to inspire people to appreciate and protect the Sound and the global environment. Over the past decade, a large percentage of the region’s 23 million people living within 50 miles of the Sound were directly affected by severe weather events, providing a timely opportunity to educate students, teachers and the public about community resilience. In a new three-year program, the Maritime Aquarium will deliver education related to environmental hazards, resilience, and the underlying science to schools from ten towns along or near Connecticut’s coast, including eight in the Natural Hazards Mitigation Plan Draft 2016-2021 for Southwestern Connecticut. In these towns as in many coastal regions, the most significant environmental threats are related to the nexus of land and water. To reflect that nexus, education will occur both in the classroom and on the water, aboard the Aquarium’s hybrid-electric research vessel, Spirit of the Sound. An exhibit featuring NOAA educational assets related to threats and resilience will also build environmental literacy as it engages Aquarium visitors. The project will be supported by an advisory board of local educators, planning and emergency management officials, representatives from Connecticut Sea Grant, the Connecticut Institute for Resilience and Climate Adaptation and the Western Connecticut Council of Governments.
Whereas the evolution of snow cover across forested mountain watersheds is difficult to predict or model accurately, the presence or absence of snow cover is easily observable and these observations contribute to improved snow models. We engaged citizen scientists to collect observations of the timing of distributed snow disappearance over three snow seasons across the Pacific Northwest, U.S.A. . The primary goal of the project was to build a more spatially robust dataset documenting the influence of forest cover on the timing of snow disappearance, and public outreach was a secondary goal
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TEAM MEMBERS:
Susan Dickerson-LangeKarla EitelLeslie DorseyTimothy LinkJessica Lundquist
This Advancing Informal Science Learning Pathways project, Using Technology to Research After Class (UTRAC), explores whether a combination of technology (e.g., iPad-enabled sensors, web-based inquiry-focused portal) and facilitated visits improves learning outcomes for rural and Native American elementary-age youth in after school programs. Expected outcomes include improved engagement, knowledge, skills, and attitudes toward science, technology, engineering, and math (STEM). Project goals include promoting STEM learning through science inquiry activities keyed to specific Next Generation Science Standards as well as improving how technology can be used to enhance learning outcomes in afterschool programs. The experimental design of this project - testing the effects of physical or virtual facilitation visits on learning outcomes - will lead to improvements in STEM learning outcomes among rural and underrepresented students. This project will employ several innovations in utilizing technology to teach STEM topics including: (i) hands-on, real-time, crowd sourced data collected by participants in their schoolyards; (ii) a pedagogic emphasis on communication of schoolyard data among and between participants; (iii) testing of motivational incentives; and (iv) partnerships between after school providers, preservice teachers, and university researchers as facilitators. The entire process will be modularized so that it can be modified in terms of place, STEM topic or student cohort. The topic focus of the project -- Life Under Snow -- is relevant to participating students, as Montana school playgrounds lie blanketed under snow for the majority of the school year; it includes elements of snow science, carbon cycle science, and a combination at the intersection of three recent literacy initiatives (e.g., Earth Science, Climate, or Energy). UTRAC will pilot and evaluate facilitated snow science/carbon cycle science activities that couple real-time schoolyard data with tools patterned after those available through WISE (Web-based Inquiry Science Environment; wise.berkeley.edu). Participants will collect and compare data with other youth participants, and researchers will use formative assessments to define interventions with potential to maximize student engagement and learning improvements among underserved youth. The project will advance understanding of informal education's potential to improve STEM engagement, knowledge, skills and attitudes by quantifying how - and to what extent - youth engage with emerging technologies iPad-enabled sensors, and crowdsourcing and visualization tools. The deliverables include a quantifying metric for learning outcomes, a training model for the iPad sensors and web application, an orientation kit, a social media portal, and database for the measurements.
The Cyberlearning and Future Learning Technologies Program funds efforts that support envisioning the future of learning technologies and advance what we know about how people learn in technology-rich environments. Development and Implementation (DIP) Projects build on proof-of-concept work that shows the possibilities of the proposed new type of learning technology, and PI teams build and refine a minimally-viable example of their proposed innovation that allows them to understand how such technology should be designed and used in the future and that allows them to answer questions about how people learn, how to foster or assess learning, and/or how to design for learning. This project is building and studying a new type of online learning community. The WeatherBlur community allows kids, teachers, scientists, fishermen/fisherwomen, and community members to learn and do science together related to the local impacts of weather and climate on their coastal communities. Members of the community propose investigations, collect and share data, and learn together. WeatherBlur is designed to be a new form of knowledge-building community, the Non-Hierarchical Online Learning Community. Unlike other citizen science efforts, there is an emphasis on having all members of the community able to propose and carry out investigations (and not just help collect data for investigations designed by expert scientists or teachers). Prior research has demonstrated important structural differences in WeatherBlur from other citizen science learning communities. The project will use social network analysis and discourse analysis to measure learning processes, and Personal Meaning Mapping and embedded assessments of science epistemology and graph interpretation skills to examine outcomes. The measures will be used to explore knowledge-building processes and the scaffolds required to support them, the negotiation of explanations and investigations across roles, and the epistemic features that drive this negotiation process. The work will be conducted using an iterative design-based research process in which the prior functioning WeatherBlur site will be enhanced with new automated prompt and notification systems that support the non-hierarchical nature of the community, as well as tools to embed assessment prompts that will gauge participants' data interpretation skills and epistemic beliefs. Exponential random graph modeling will be used to analyze the social network analysis data and test hypotheses about the relationship between social structures and outcomes.