C-RISE will create a replicable, customizable model for supporting citizen engagement with scientific data and reasoning to increase community resiliency under conditions of sea level rise and storm surge. Working with NOAA partners, we will design, pilot, and deliver interactive digital learning experiences that use the best available NOAA data and tools to engage participants in the interdependence of humans and the environment, the cycles of observation and experiment that advance science knowledge, and predicted changes for sea level and storm frequency. These scientific concepts and principles will be brought to human scale through real-world planning challenges developed with our city and government partners in Portland and South Portland, Maine. Over the course of the project, thousands of citizens from nearby neighborhoods and middle school students from across Maine’s sixteen counties, will engage with scientific data and forecasts specific to Portland Harbor—Maine’s largest seaport and the second largest oil port on the east coast. Interactive learning experiences for both audiences will be delivered through GMRI’s Cohen Center for Interactive Learning—a state-of-the-art exhibit space—in the context of facilitated conversations designed to emphasize how scientific reasoning is an essential tool for addressing real and pressing community and environmental issues. The learning experiences will also be available through a public web portal, giving all area residents access to the data and forecasts. The C-RISE web portal will be available to other coastal communities with guidance for loading locally relevant NOAA data into the learning experience. An accompanying guide will support community leaders and educators to embed the interactive learning experiences effectively into community conversations around resiliency. This project is aligned with NOAA’s Education Strategic Plan 2015-2035 by forwarding environmental literacy and using emerging technologies.
Over three years beginning in January 2016, the Science Museum of Virginia will launch a new suite of public programming entitled “Learn, Prepare, Act – Resilient Citizens Make Resilient Communities.” This project will leverage federally funded investments at the Museum, including a NOAA-funded Science On a Sphere® platform, National Fish and Wildlife-funded Rainkeepers exhibition, and the Department of Energy-funded EcoLab, to develop public programming and digital media messaging to help the general public understand climate change and its impacts on Virginia’s communities and give them tools to become resilient to its effects. Home to both the delicate Chesapeake Bay ecosystem and a highly vulnerable national shoreline, Virginia is extremely susceptible to the effects of climate change and extreme weather events. It is vital that citizens across the Commonwealth understand and recognize the current and future impacts that climate variability will have on Virginia’s economy, natural environment, and human health so that they will be better prepared to respond. In collaboration with NOAA Chesapeake Bay Office, George Mason University’s Center for Climate Change Communication, Virginia Institute for Marine Science, Public Broadcasting Service/National Public Radio affiliates, and Resilient Virginia, the Museum will use data from the National Climatic Data Center and Virginia Coastal Geospatial and Educational Mapping System to develop and deliver new resiliency-themed programming. This will include presentations for Science On a Sphere® and large format digital Dome theaters, 36 audio and video digital media broadcast pieces, two lecture series, community preparedness events, and a Resiliency Checklist and Certification program. This project supports NOAA’s mission goals to advance environmental literacy and share its vast knowledge and data with others.
This project team will develop and test a prototype of Planet 3, a multi-media online platform to apply real world problems (e.g., pollution, overpopulation) to middle school earth and life science learning. The prototype will include videos, simulations, and games to allow opportunities for students to explore problem sets, collect and analyze data, and draw conclusions. At the end of Phase I in a pilot study with two classrooms, the researchers will examine whether the prototype functions as planned, where teachers can implement the prototype within classroom practice, and if students are engaged while examining real-world problems.
Social media is increasingly being used by science communicators, journalists and government agencies to engage in discourse with a range of publics. Despite a growing body of literature on Twitter use, the communication of science via Twitter is comparatively under explored. This paper examines the prominence of scientific issues in political debate occurring on Twitter during the 2013 and 2016 Australian federal election campaigns. Hashtracking of the umbrella political hashtag auspol was used to capture tweets during the two campaign periods. The 2013 campaign was particularly relevant as a
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TEAM MEMBERS:
Merryn McKinnonDavid SemmensBrenda MoonInoka AmarasekaLea Bolliet
Changes in household-level actions in the U.S. have the potential to reduce rates of greenhouse gas (GHG) emissions and climate change by reducing consumption of food, energy and water (FEW). This project will identify potential interventions for reducing household FEW consumption, test options in participating households in two communities, and collect data to develop new environmental impact models. It will also identify household consumption behavior and cost-effective interventions to reduce FEW resource use. Research insights can be applied to increase the well-being of individuals at the household level, improve FEW resource security, reduce climate-related risks, and increase economic competitiveness of the U.S. The project will recruit, train, and graduate more than 20 students and early-career scientists from underrepresented groups. Students will be eligible to participate in exchanges to conduct interdisciplinary research with collaborators in the Netherlands, a highly industrialized nation that uses 20% less energy and water per person than the U.S.
This study uses an interdisciplinary approach to investigate methods for reducing household FEW consumption and associated direct and indirect environmental impacts, including GHG emissions and water resources depletion. The approach includes: 1) interactive role-playing activities and qualitative interviews with homeowners; 2) a survey of households to examine existing attitudes and behaviors related to FEW consumption, as well as possible approaches and barriers to reduce consumption; and 3) experimental research in residential households in two case-study communities, selected to be representative of U.S. suburban households and appropriate for comparative experiments. These studies will iteratively examine approaches for reducing household FEW consumption, test possible intervention strategies, and provide data for developing systems models to quantify impacts of household FEW resource flows and emissions. A FEW consumption-based life cycle assessment (LCA) model will be developed to provide accurate information for household decision making and design of intervention strategies. The LCA model will include the first known farm-to-fork representation of household food consumption impacts, spatially explicit inventories of food waste and water withdrawals, and a model of multi-level price responsiveness in the electricity sector. By translating FEW consumption impacts, results will identify "hot spots" and cost-effective household interventions for reducing ecological footprints. Applying a set of climate and technology scenarios in the LCA model will provide additional insights on potential benefits of technology adoption for informing policymaking. The environmental impact models, household consumption tracking tool, and role-playing software developed in this research will be general purpose and publicly available at the end of the project to inform future education, research and outreach activities.
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TEAM MEMBERS:
David WatkinsBuyung AgusdinataChelsea SchellyRachael ShwomJenni-Louise Evans
The Fluid Earth Viewer (FEVer), an interactive and visually appealing web application that will allow users to visualize current and past conditions of our planet's atmosphere and oceans will be built via this award. This free web application, available to anyone with an internet connection, will directly impact approximately 2,000 individuals in-person through three field tests and is expected to reach many more online.
FEVer will be an extension of an existing open-source web application, and the PIs will add polar data sets, extended options in the user interface, and the ability to view historical climate/weather data to the existing "earth" app. It will be a vehicle of modern Earth science communication, making information most often used by the scientific community accessible and engaging to broader communities. In particular, it will provide hands-on visualization of the important climatic role of the polar-regions, their connections to lower latitudes, and the changes they are undergoing. A companion website, FEVer-Ed, will provide background, educational support, and opportunities for additional learning through a gallery of historically interesting atmospheric and oceanic events. FEVer will serve as a gateway to data sets that have otherwise been inaccessible to audiences outside of the research community. While a number of large data sets are included in this proposal (regional and global operational weather models/reanalyses), the platform is scalable to include other data such as ice sheet and glacier dynamics.
This project is partially funded by the Advancing Informal STEM Learning (AISL) program, which seeks to advance new approaches to, and evidence-based understanding of, the design and development of STEM learning in informal environments. This includes providing multiple pathways for broadening access to and engagement in STEM learning experiences, advancing innovative research on and assessment of STEM learning in informal environments, and developing understandings of deeper learning by participants.
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.
This early-stage design and development, integrated media and research project will contribute important new understandings to the informal science learning literature by exploring science engagement on social media when integrated with broadcast television. It will help answer questions including: What does such engagement look like? Who participates? How and why does it happen? and What is the degree or depth of engagement? The project builds on the previous successful work by WGBH nationally distributing the television series NOVA scienceNOW and the research expertise of EDC. WGBH's NOVA scienceNOW program will collaborate with EDC to develop new metrics to understand how and why learners engage with science on social media. Deliverables will include six one-hour episodes of NOVA scienceNOW, short online videos, moderated online discussion events, and an online film festival. A new social Media Initiative will develop six live broadcast microblogging events, six post-broadcast online discussion events, daily social media updates, and an online film festival that will feature user generated videos. A range of STEM content in the videos and online posts will be framed around big science and engineering questions such as animal communication and survival systems, the biology of sleep, climate change, new technologies, energy, genetics, and natural disasters. The continued innovations and expansion of social media channels provides significant new opportunities for providing learner's access to high quality science content, researchers, and opportunities to participate in science. In the first phase of this work to deepen the evidence based understanding of how social media supports informal science engagement, NOVA and EDC will collaborate to develop new measurement instruments: (1) a Network Profile to quantitatively represent the size and activity of NOVA's social media network; (2) an Informal Science Engagement (ISE) index to measure the degree of engagement by coding and analyzing conversations and posts; (3) a Follower Profile to assess the degree of activity and the nature of the engagement; and (4) a Science Social Media Engagement survey instrument. They will then use these measures and data collection protocols to explore whether and how the initiative might influence science engagement. External expert reviewers with content and methodological expertise will review all aspects of the project at critical junctures. This project will contribute important new knowledge and research instruments and methods to better understand how the learning opportunities of social media channels can be realized most effectively. This has significant potential for broad and lasting benefits to society as well as advancing the informal science learning field.
In this full-scale research and development project, Oregon State University (OSU), Oregon Sea Grant (OSG) and the Hatfield Marine Science Center Visitors Center (HMSCVC) is designing, developing, implementing, researching and evaluating a cyberlaboratory in a museum setting. The cyberlaboratory will provide three earth and marine science learning experiences with research and evaluation interwoven with visitor experiences. The research platform will focus on: 1) a climate change exhibit that will enable research on identity, values and opinion; 2) a wave tank exhibit that will enable research on group dynamics and problem solving in interactive engineering challenges; and 3) remote sensing exhibits that will enable research on visitor interactions through the use of real data and simulations. This project will provide the informal science educaton community with a suite of tools to evaluate learning experiences with emerging technologies using an iterative process. The team will also make available to the informal science community their answers to the following research questions: For the climate change exhibit, "To what extent does customizing content delivery based on real-time visitor input promote learning?" For the wave tank exhibit, "To what extent do opportunities to reflect on and share experiences promote STEM reasoning processes at a build-and-test exhibit?" For the data-sensing exhibit, "Can visitors' abilities to explain or use visualizations be improved by shaping their visual searches of images?" Mixed-methods using interviews, surveys, behavioral instruments, and participant observations will be used to evaluate the overall program. Approximately 60-100 informal science education professionals will discuss and test the viability of the exhibit's evaluation tools. More than 150,000 visitors, along with community members and local middle and high school students, will have the opportunity to participate in the learning experiences at the HMSCVC. This work contributes to the fields of cyberlearning and informal science education. This project provides the informal science education field with important knowledge about learning, customized content delivery and evaluation tools that are used in informal science settings.
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.