In this collaborative project, a university research lab and children's science museum work together to design, implement, study, and revise a week-long data science camp for middle school age students, data science learning assessment items and a facilitator training curriculum.
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.
DATE:
-
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
DATE:
TEAM MEMBERS:
Remy DouHeidi CianZahra HazariPhilip SadlerGerhard Sonnert
resourceevaluationMuseum and Science Center Exhibits
The linked repository contains select resources from the SICIIT NSF project (Supporting Science and Engineering Identity Change in Immersive Interactive Technologies). The project did not reach its main objective, mainly due to disruptions caused by COVID, but we hope that the materials will be a useful resource for follow-up research.
DATE:
TEAM MEMBERS:
Stefan RankAyana AllenGlen MuschioAroutis FosterKapil Dandekar
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.
DATE:
-
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.
The pilot and feasibility study will develop instructional workshops for an adult population of quilters to introduce them to computational thinking. By leveraging pre-existing social structures, skill sets, and engagement in quilting, the researchers hope to help participants develop computer science and computational thinking knowledge and skills.
This poster was presented at the 2021 NSF AISL Awardee Meeting.