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.
Mobile technology can be used to scaffold inquiry-based learning, enabling learners to work across settings and times, singly or in collaborative groups. It can expand learners’ opportunities to understand the nature of inquiry whilst they engage with the scientific content of a specific inquiry. This Sharples et al. paper reports on the use of the mobile computer-based inquiry toolkit nQuire. Teachers found the tool useful in helping students to make sense of data from varied settings.
The National Oceanic and Atmospheric Administration (NOAA) and the Exploratorium began an exciting long-term alliance in 2009 to present climate and ocean sciences to the public. NOAA’s mission is to understand and predict changes in climate, weather, and coasts using cutting-edge research and high-tech instrumentation, and to share its knowledge with others. Teaming up with the Exploratorium enables NOAA to explore new methods of communicating its work using the creativity and educational expertise of the museum. The partnership involves codeveloping exhibits, online media, public programs, and research about learning, and it also provides professional development opportunities for NOAA scientists. Some examples of partnership projects include the Scientists-in-Residence Program, the Wired Pier Project, the Deep-Water Dock at the Piers, and the Okeanos Explorer exhibit.