The popularity of the anti-vax movement in the United States and elsewhere is the cause of new lethal epidemics of diseases that are fully preventable by modern medicine [Benecke and DeYoung, 2019]. Creationism creeps into science classrooms with the aim of undermining the teaching of evolution through legal obligations or school boards’ decisions to present both sides of a debate largely foreign to the scientific community [Taylor, 2017]. And one simply has to turn on the TV and watch so-called science channels to be bombarded with aliens, ghosts, cryptids and miracles as though they are
Peer production projects involve people in many tasks, from editing articles to analyzing datasets. To facilitate mastery of these practices, projects offer a number of learning resources, ranging from project-defined FAQsto individually-oriented search tools and communal discussion boards. However, it is not clear which project resources best support participant learning, overall and at different stages of engagement. We draw on Sørensen's framework of forms of presence to distinguish three types of engagement with learning resources: authoritative, agent-centered and communal. We assigned
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TEAM MEMBERS:
Corey Brian JacksonCarsten OsterlundKevin CrowstonMahboobeh HarandiLaura Trouille
The SciGirls in Space Front End Evaluation included surveys with project advisors, girls and families about the nature and extent of partner program offerings to help inform production of media and use of media in outreach. Question 1: To what extent do advisors, girls and their family members find the girls and professionals featured in the (existing) episodes and role model videos to be effective role models? Question 2: To what extent do they find episode topics and stories relevant to their everyday lives?
It is estimated that there could be 40 billion earth-sized planets orbiting in the habitable zones of stars in the Milky Way. Major advances in long range telescopes have allowed astronomers to identify thousands of exoplanets in recent decades, and the discovery of new exoplanets is a now a common occurrence. Public excitement for the discoveries grown alongside these discoveries, thus opening new possibilities for inspiring a new generation of scientists and engineers that may dream of one day visiting these planets. This project investigates the use of interactive, intelligent educational technologies to generate interest in STEM by allowing learners to explore and even create their own exoplanets. Research will occur across several informal learning contexts, including summer camps, after school programs, planetarium shows, and at home. The approach is based on the idea of "What if?"questions about Earth (e.g., "What if the Moon did not exist?"), designed to trigger interest in STEM and frame exploratory and elaborative discussions around hypothetical science questions that are subsequently linked to the search for habitable exoplanets. Learners are able to interact with and explore scientifically accurate simulations of alternative versions of Earth, while making observations and posing explanations for what they see. Technology-based informal learning experiences designed to act as triggers for and sustainment of interest in STEM have the potential to plug the leaky STEM pipeline, and thus have profound implications for the future of science and technology in the United States.
The project seeks to advance the science of designing technologies for promoting interest in STEM and informal astronomy education in several ways. First, the project will develop simulations for exploratory learning about astronomy and planetary science. These simulations will present hypothetical worlds based on what-if questions and feasible models of known exoplanets, thus giving learners a chance to better understand the challenges of finding a habitable world and learning about what is needed to survive there. Second, a new PBS NOVA Lab will be developed that will focus on Exoplanet education. This web-based activity has the potential to reach millions of learners and will help them understand how planets are formed and the requirements for supporting life. Learners who use the lab will have an opportunity to invent their own exoplanets and export them for first-person exploration. Third, researchers on the project will design and implement Artificial Intelligence-based pedagogical agents to support learning and promote interest. These agents will inhabit the simulations with the learner, acting as a coach and guide, and be designed to be culturally responsive and personalized based on learner preferences. Fourth, interactive exoplanet-focused planetarium shows, that will involve live interaction with simulations, will take place at the Fiske Planetarium (Boulder, CO). Finally, the project will develop a server-based infrastructure for tracking and supporting long term development of interest in STEM. This back-end will track fine-grained behaviors, including movement, actions, and communications in the simulations. Such data will reveal patterns about how interest develops, how learners engage in free-choice learning activities, and how they interact with agents and peers in computer simulations. A design-based research methodology will be employed to assess the power of these different experiences to trigger interest and promote learning of astronomy. A range of different pathways for interest in STEM will therefore be considered and assessed. Research will measure the power of these experiences to trigger interest in STEM and promote re-engagement over time. Innovation lies in the use of engaging and intelligent technologies with thought-provoking pedagogy as a method for extended engagement of diverse young learners in STEM. Project research and educational resources will be widely disseminated to researchers, designers developers and the general public via peer-reviewed research journals, conference presentations, informal STEM education networks of science museums, children's museums, Fab Labs, and planetariums, and public media such as public television's NOVA science program website.
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.
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TEAM MEMBERS:
H Chad LaneNeil CominsJorge Perez-GallegoDavid Condon
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.
The Space and Earth Informal STEM Education (SEISE) project, led by the Arizona State University with partners Science Museum of Minnesota, Museum of Science, Boston, and the University of California Berkeley’s Lawrence Hall of Science and Space Sciences Laboratory, is raising the capacity of museums and informal science educators to engage the public in Heliophysics, Earth Science, Planetary Science, and Astrophysics, and their social dimensions through the National Informal STEM Education Network (NISE Net). SEISE will also partner on a network-to-network basis with other existing coalitions and professional associations dedicated to informal and lifelong STEM learning, including the Afterschool Alliance, National Girls Collaborative Project, NASA Museum Alliance, STAR_Net, and members of the Association of Children’s Museums and Association of Science-Technology Centers. The goals for this project include engaging multiple and diverse public audiences in STEM, improving the knowledge and skills of informal educators, and encouraging local partnerships.
In collaboration with the NASA Science Mission Directorate (SMD), SEISE is leveraging NASA subject matter experts (SMEs), SMD assets and data, and existing educational products and online portals to create compelling learning experiences that will be widely use to share the story, science, and adventure of NASA’s scientific explorations of planet Earth, our solar system, and the universe beyond. Collaborative goals include enabling STEM education, improving U.S. scientific literacy, advancing national educational goals, and leveraging science activities through partnerships. Efforts will focus on providing opportunities for learners explore and build skills in the core science and engineering content, skills, and processes related to Earth and space sciences. SEISE is creating hands-on activity toolkits (250-350 toolkits per year over four years), small footprint exhibitions (50 identical copies), and professional development opportunities (including online workshops).
Evaluation for the project will include front-end and formative data to inform the development of products and help with project decision gates, as well as summative data that will allow stakeholders to understand the project’s reach and outcomes.