Arecibo C3 will serve as a collaborative hub for STEM discovery and exploration by building upon existing programs and opportunities established at the Arecibo site by previous NSF programs, while also creating new STEM education, research, and outreach programs and initiatives. The goals for the Center are to (1) promote STEM education, learning, and teaching; (2) support fundamental and applied STEM and STEM education research; (3) broaden participation in STEM; and (4) build and strengthen collaborations and partnerships.
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TEAM MEMBERS:
Jose Agosto RiveraJoseph Carroll-MirandaJaime Abreu RamosAmilcar VelezJason WilliamsCristina Fernandez-MarcoWanda Diaz MercedAnuchka RamosPatricia Ordonez
Informal STEM learning experiences (ISLEs), such as participating in science, computing, and engineering clubs and camps, have been associated with the development of youth’s science, technology, engineering, and mathematics interests and career aspirations. However, research on ISLEs predominantly focuses on institutional settings such as museums and science centers, which are often discursively inaccessible to youth who identify with minoritized demographic groups. Using latent class analysis, we identify five general profiles (i.e., classes) of childhood participation in ISLEs from data
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TEAM MEMBERS:
Remy DouHeidi CianZahra HazariPhilip SadlerGerhard Sonnert
Mathematizing, Visualizing, and Power (MVP): Appalachian Youth Becoming Data Artists for Community Learning is a three-year Advancing Informal STEM Learning, Innovations and Development, project that focuses on community-centered data exploration catalyzed by youth. The project develops statistical artistry among young people in East Tennessee Appalachian communities and enables these youth to share their data visualizations with their communities to foster collective reflection and understanding. The creative work generated by the MVP project will be compelling in two ways, both as statistical art and as powerful statements giving voice to the experience of communities. Critical aspects of the MVP model include (1) youth learning sessions that position youth as owners of data and producers of knowledge and (2) Community Learning Events that support community learning as youth learning occurs. The MVP project has a primary focus on broadening the STEM participation of underrepresented communities of Appalachia. The project’s mission is to increase the learning and life outcomes of young people and communities of Appalachia by creating a meaningful foundation of data science and collective data exploration. The University of Tennessee partners with Pellissippi State Community College, Drexel University, and the Boys & Girls Club of the Tennessee Valley to bring together a convergent team of community members, practitioners, and professionals, with the expertise to carry out the project. The project will impact approximately 120 youth and 3800 of their East Tennessee community members. The research generated will inform how to engage community members in learning about community issues through the exploration of datasets relevant to participants.
The field of STEM education is in urgent need of knowledge about effective models to inspire community-based data exploration with young people as leaders in these efforts. The MVP project includes engaging youth with meaningful problems, building a discourse community with possibilities for action, re-positioning youth as knowledge producers within their own communities, leveraging linguistic and cultural resources of the youth participants and their communities, and implementing critical events that support substantial interaction between youth, community members, and the data visualizations. MVP builds on the idea that the design of data visualizations requires an understanding of both data science and artistic design. Research will inform the model of community engagement, examine data artists’ identities, and document community learning. The MVP model will be designed, developed, tested, and refined through three cycles of design-based research. The overarching research question guiding these cycles is: What affordances (and delimitations) related to identity and learning does the model provide for MVP Youth and community members? Data sources for the project include: fieldnotes, portfolios created by MVP Youth, youth pre/post interviews, observations of the learning sessions, a project documentary, surveys for youth and community members, interviews with community members, and audience feedback. The National Institute for STEM Evaluation and Research (NISER) will provide formative and summative evaluation about project activities. Formative feedback will be integrated into the ongoing research cycles. The research conducted will inform (1) the community learning model; (2) the integrated pedagogy and curriculum of the MVP Youth learning sessions that emphasize data science through design arts; and, (3) research on community learning and youth identity. Findings will be shared through conferences, academic and practitioner-focused journals, a video documentary, a Summit on Engaging Youth and Communities in Data, and a project website.
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TEAM MEMBERS:
Lynn HodgeElizabeth DyerJoy BertlingCarlye Clark
resourceprojectProfessional Development, Conferences, and Networks
The New York Hall of Science (NYSCI) will convene a two-day participatory design conference of to identify research and education opportunities in informal settings for supporting literacy concerning Artificial Intelligence (AI), especially for diverse and underserved youth whose communities are impacted by the bias in some AI processes. AI uses computer systems that simulate human intelligence. AI systems impact nearly every aspect of daily living, performing tasks underlying navigation apps, facial recognition, e-payments, and social media. AI can perpetuate inequities and biased outcomes in the culture at large. The conference will explore how to promote engagement and conceptual learning among youth about how AI works and what skills are needed to critically use and apply AI. The conference will also explore ways to support the interests of diverse and underserved children and youth in shaping AI and joining the growing STEM workforce that will use AI in their professions.
The conference will identify key features and needs with respect to AI literacy and explore the specific roles that informal learning can play in advancing AI literacy for youth in diverse and underserved communities. Participants in the conference will include designers, learning scientists, researchers, informal and formal educators, and science center professionals. Attendees will work in separate teams and as a group to explore and critique existing AI tools and learning frameworks, discuss lessons learned from promising AI literacy programs, and identify design principles and future directions for research. Specific attention will be paid to informal mechanisms of engagement, promising networks, and research-practice partnerships that take advantage of the unique affordances of informal learning and community services to accelerate AI literacy for historically excluded youth. The insights gained from this work will result in a set of research and programmatic priorities for informal institutions to promote AI literacy in culturally responsive ways. The resulting published guide and community events will broadly disseminate priorities and design principles generated by this convening to help informal learning institutions and community learning organizations identify both assets and priorities for addressing diversity, equity, access, and inclusion issues related to AI literacy.
This poster was presented at the 2021 NSF AISL Awardee Meeting.
Today’s young people have a personal stake in their ability to function with data. Future job prospects might hinge on their ability to participate in the new data economy. But equally, young people are themselves the subjects of data. The datafication of young people’s lives leads to profound questions about childhood, technology, and the equity of access to STEM learning around data, one of which is this: How might young people be empowered in a data-centric world?
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TEAM MEMBERS:
Leanne BowlerMark RosinIrene Lopatovska
This poster was presented at the 2021 NSF AISL Awardee Meeting.
Collaborative robots – cobots – are designed to work with humans, not replace them. What learning affordances are created in educational games when learners program robots to assist them in a game instead of being the game? What game designs work best?
Maker Education scholarship is accumulating increasingly complex understandings of the kinds of learning associated with maker practices along with principles and pedagogies that support such learning. However, even as large investments are being made to spread maker education, there is little understanding of how organizations that are intended targets of such investments learn to develop new maker related educational programs. Using the framework of Expansive Learning, focusing on organizational learning processes resulting in new and unfolding forms of activity, this paper begins to fill
Overlaying Computer Science (CS) courses on top of inequitable schooling systems will not move us toward “CS for All.” This paper prioritizes the perspectives of minoritized students enrolled in high school CS classrooms across a large, urban school district in the Western United States, to help inform how CS can truly be for all.
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TEAM MEMBERS:
Jean RyooTiera TanksleyCynthia EstradaJane Margolis
Virtual Reality (VR) shows promise to broaden participation in STEM by engaging learners in authentic but otherwise inaccessible learning experiences. The immersion in authentic learner environments, along with social presence and learner agency, that is enabled by VR helps form memorable learning experiences. VR is emerging as a promising tool for children with autism. While there is wide variation in the way people with autism present, one common set of needs associated with autism that can be addressed with VR is sensory processing. This project will research and model how VR can be used to minimize barriers for learners with autism, while also incorporating complementary universal designs for learning (UDL) principles to promote broad participation in STEM learning. As part of its overall strategy to enhance learning in informal environments, the Advancing Informal STEM Learning (AISL) program funds innovative research, approaches, and resources for use in a variety of settings. This project will build on a prototype VR simulation, Mission to Europa Prime, that transports learners to a space station for exploration on Jupiter's moon Europa, a strong candidate for future discovery of extraterrestrial life and a location no human can currently experience in person. The prototype simulation will be expanded to create a full, immersive STEM-based experience that will enable learners who often encounter cognitive, social, and emotional barriers to STEM learning in public spaces, particularly learners with autism, to fully engage and benefit from this STEM-learning experience. The simulation will include a variety of STEM-learning puzzles, addressing science, mathematics, engineering, and computational thinking through authentic and interesting problem-solving tasks. The project team's learning designers and researchers will co-design puzzles and user interfaces with students at a post-secondary institute for learners with autism and other learning differences. The full VR STEM-learning simulation will be broadly disseminated to museums and other informal education programs, and distributed to other communities.
Project research is designed to advance knowledge about VR-based informal STEM learning and the affordances of VR to support learners with autism. To broaden STEM participation for all, the project brings together research at the intersection of STEM learning, cognitive and educational neuroscience, and the human-technology frontier. The simulation will be designed to provide agency for learners to adjust a STEM-learning VR experience for their unique sensory processing, attention, and social anxiety needs. The project will use a participatory design process will ensure the VR experience is designed to reduce barriers that currently exclude learners with autism and related conditions from many informal learning opportunities, broadening participation in informal STEM learning. Design research, usability, and efficacy studies will be conducted with teens and adults at the Pacific Science Center and Boston Museum of Science, which serve audiences with autism, along with the general public. Project research is grounded in prior NSF-funded research and leverages the team's expertise in STEM learning simulations, VR development, cognitive psychology, universal design, and informal science education, as well as the vital expertise of the end-user target audience, learners with autism. In addition to being shared at conferences, the research findings will be submitted for publication to peer-reviewed journals for researchers and to appropriate publications for VR developers and disseminators, museum programs, neurodiverse communities and other potentially interested parties.
This Innovations in Development award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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TEAM MEMBERS:
Teon EdwardsJodi Asbell-ClarkeJamie LarsenIbrahim Dahlstrom-Hakki
This paper contributes a theoretical framework informed by historical, philosophical and ethnographic studies of science practice to argue that data should be considered to be actively produced, rather than passively collected. We further argue that traditional school science laboratory investigations misconstrue the nature of data and overly constrain student agency in their production. We use our “Data Production” framework to analyze activity of and interviews with high school students who created data using sensors and software in a ninth-grade integrated science class. To understand the