In a unique collaboration between PBS NewsHour and Indij Public Media (the parent company of ICT, formerly known as Indian Country Today), this project will put the perspectives and the reporting of Indigenous communities front and center through their co-creation of digital and broadcast segments.
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
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 MagerkoDuri LongJessica Roberts
Milwaukee has established itself as a leader in water management and technology, hosting a widely recognized cluster of industrial, governmental, nonprofit, and academic activity focused on freshwater. At the same time, Milwaukee faces a wide range of challenges with freshwater, some unique to the region and others common to cities throughout the country. These challenges include vulnerability to flooding and combined sewer overflows after heavy rainfall, biological and pharmaceutical contamination in surface water, lead in drinking water infrastructure, and inequity in access to beaches and other recreational water amenities. Like other cities, Milwaukee grapples with the challenges global climate change imposes on urban water systems, including changing patterns of precipitation and drought.
These problems are further complicated by Milwaukee's acute racial and economic residential segregation. With a population of approximately 595,000, embedded within a metropolitan area of over 1.5 million, Milwaukee remains one of the country's most segregated cities. There is increasing urgency to engage the public--and especially those who are most vulnerable to environmental impacts--more deeply in the stewardship of urban water and in the task of creating sustainable urban futures. The primary goal of this four-year project is to foster community-engaged learning and environmental stewardship by developing a framework that integrates art with Science, Technology, Engineering, and Mathematics (STEM) experiences along with geography, water management, and social science. Synergies between STEM learning and the arts suggest that collaborations among artists, scientists, and communities can open ways to bring informal learning about the science of sustainability to communities.
WaterMarks provides an artist generated conceptual framework developed by Mary Miss / City as Living Laboratory (CALL) to help people better understand their relationship to the water systems and infrastructure that support their lives. Project activities include artist/scientist/community member-led Walks, which are designed to engage intergenerational participants both from the neighborhoods and from across the city, in considering the conditions, characteristics, histories, and ecosystems of neighborhoods. Walks are expanded upon in Workshops with residents, local scientists/experts, and other stakeholders, and include exploring current water-related environmental challenges and proposing solutions. The Workshops draw on diverse perspectives, including lived experience, scientific knowledge, and policy expertise. Art projects created by local artists amplify community engagement with the topics, including programming for teens and young adults. Free Wi-Fi will be integrated into various Marker sites around the city providing access to online, self-guided learning opportunities exploring the water systems and issues facing surrounding neighborhoods. Current programming focuses primarily on Milwaukee's predominantly African American near North Side and the predominantly Latinx/Hispanic near South Side. Many neighborhoods in these sections are vulnerable to such problems as frequent flooding, lead contamination in drinking water, inequities in safety and maintenance of green space, and less access to Lake Michigan, the city's primary natural resource and recreational amenity.
The WaterMarks project advances informal STEM learning in at least two ways. First, while the WaterMarks project is designed to fit Milwaukee, the project includes the development of an Adaptable Model Guide. The Guide is designed so that other cities can modify and employ its inclusive structure, programming, and process of collaboration among artists, scientists, partner organizations, and residents to promote citywide civic engagement in urban sustainability through the combination of informal STEM learning and public art. The Guide will be developed by a Community-University Working Group (CULab) hosted by UW-Milwaukee's Center for Community-Based Learning, Leadership, and Research and made up of diverse community and campus-wide stakeholders. In addition to overseeing the Guide’s creation, CULab will conceptualize onboarding and mentorship strategies for new participants as well as a framework for the program’s expansion and sustainability.
Second, through evaluation and research, the project will build a theoretical model for the relationships among science learning, engagement with the arts, and the distinctive contexts of different neighborhoods within an urban social-ecological system. The evaluation team, COSI’s Center for Research and Evaluation, and led by Co-PI Donnelly Hayde, aims to conduct formative, summative, and process evaluation of the Watermarks project, with the additional goal of producing evaluative research findings that can contribute to the broader field of informal learning. Evaluation foci include: How does the implementation of WaterMarks support positive outcomes for the project’s communities and the development of an adaptable model for city-scale informal science learning about urban environments? 2. To what extent do the type and degree of outcome-related change experienced by participating community residents vary across and/or between project sites? What factors, if any, appear to be linked to these changes? 3. To what extent and in what ways do the activities of the WaterMarks projects appear to have in situ effects related to the experience of place at project sites?
The project’s research team led by PI Ryan Holifield and Co-PI Woonsup Choi, will investigate how visual artistic activities introduced by the programming team as part of the Walks (and potentially other engagement activities) interact with personal, sociocultural, and physical contexts to produce distinctive experiences and outcomes of informal science learning about urban water systems. The aim of the research will be to synthesize the results from the different WaterMarks sites into an analysis generalizable beyond specific neighborhoods and applicable to other cities. The project's research questions include: 1. How does participation in Walks focused on visual artistic activities affect outcomes and experiences of informal STEM learning about urban water systems? 2. How do outcomes and experiences of informal STEM learning vary across different urban water topics, participants from different demographic groups, and contrasting sociocultural and biophysical contexts?
This Innovations in Development project is led by the University of Wisconsin-Milwaukee (UWM), in collaboration with City as Living Laboratory (CALL) and the COSI Center for Research and Evaluation.