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resource project Informal/Formal Connections
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 Rivera Joseph Carroll-Miranda Jaime Abreu Ramos Amilcar Velez Jason Williams Cristina Fernandez-Marco Wanda Diaz Merced Anuchka Ramos Patricia Ordonez
resource project Public Programs
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 Hodge Elizabeth Dyer Joy Bertling Carlye Clark
resource project Exhibitions
Artificial intelligence (AI) is in many of our everyday activities—from unlocking phones to running Internet searches to parking cars. Yet, most instruction on how AI works is only in computer science courses. The unique role that AI plays in making decisions that affect human lives heightens the need for education approaches that promote public AI literacy. Little research has been done to understand how we can best teach AI in informal learning spaces. This project will engage middle school age youth in learning abouts AI through interaction with museum exhibits in science and technology centers. The exhibits employ embodied interactions and creative making activities that involve textiles, music making, and interactive media. The research will build on three exhibit prototypes that teach about concepts including bias in data in machine learning, AI decision-making processes, and how AI represents knowledge. Female-identifying and Title 1 youth will be recruited as participants during the exhibit design iterations and testing. The project is 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

Researchers will explore two key research questions: 1) How can the design of interactive museum exhibits encourage interest development in and learning about AI among learners without a Computer Science background by using embodiment and creative making? and 2) How do embodied interaction and creative making mediate learning about AI in informal learning environments? The project will take a design-based research approach, iteratively building on existing exhibit prototypes and testing them in-situ with learners. Data sources and modes of analysis will include retrospective surveys to assess interest, content knowledge gain, creativity, learning talk analysis of audio recordings, and coding of embodied movements in video recordings. Learning talk analysis will identify instances of joint sensemaking during naturalistic interactions with our exhibit to reveal connections between sensemaking talk; learners' behaviors and embodied actions during real-time collaborative knowledge building; and outcomes in knowledge, interest, and creativity measures as elicited in retrospective surveys. The final set of exhibits will be rigorously evaluated with over 500 museum visitors. The key contributions of this work will include a set of rigorously tested exhibits, publicly available exhibit designs, a set of design guidelines for developing AI literacy museum exhibits, and an improved understanding of the relationship between AI-related learning and interest development, embodiment, and creativity.
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TEAM MEMBERS: Brian Magerko Duri Long Jessica Roberts