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
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
This project investigates long-term human-robot interaction outside of controlled laboratory settings to better understand how the introduction of robots and the development of socially-aware behaviors work to transform the spaces of everyday life, including how spaces are planned and managed, used, and experienced. Focusing on tour-guiding robots in two museums, the research will produce nuanced insights into the challenges and opportunities that arise as social robots are integrated into new spaces to better inform future design, planning, and decision-making. It brings together researchers from human geography, robotics, and art to think beyond disciplinary boundaries about the possible futures of human-robot co-existence, sociality, and collaboration. Broader impacts of the project will include increased accessibility and engagement at two partner museums, interdisciplinary research opportunities for both undergraduate and graduate students, a short video series about the current state of robotic technology to be offered as a free educational resource, and public art exhibitions reflecting on human-robot interactions. This project will be of interest to scholars of Science and Technology Studies, Human Robotics Interaction (HRI), and human geography as well as museum administrators, educators and the general public.
This interdisciplinary project brings together Science and Technology Studies, Human Robotics Interaction (HRI), and human geography to explore the production of social space through emerging forms of HRI. The project broadly asks: How does the deployment of social robots influence the production of social space—including the functions, meanings, practices, and experiences of particular spaces? The project is based on long-term ethnographic observation of the development and deployment of tour-guiding robots in an art museum and an earth science museum. A social roboticist will develop a socially-aware navigation system to add nuance to the robots’ socio-spatial behavior. A digital artist will produce digital representations of the interactions that take place in the museum, using the robot’s own sensor data and other forms of motion capture. A human geographer will conduct interviews with museum visitors and staff as well as ethnographic observation of the tour-guiding robots and of the roboticists as they develop the navigation system. They will produce an ethnographic analysis of the robots’ roles in the organization of the museums, everyday practices of museum staff and visitors, and the differential experiences of the museum space. The intellectual merits of the project consist of contributions at the intersections of STS, robotics, and human geography examining the value of ethnographic research for HRI, the development of socially-aware navigation systems, the value of a socio-spatial analytic for understanding emerging forms of robotics, and the role of robots within evolving digital geographies.
This project is jointly funded by the Science and Technology Studies program in SBE and Advancing Informal STEM Learning (AISL) Program in EHR.
The AI behind Virtual Humans Exhibit aims to communicate to the public about the capabilities and impact of artificial intelligence (AI) through AI technologies used in Virtual Humans including facial recognition and natural language processing. AI has and will continue to profoundly impact society in the United States and around the globe. It is important to prepare the nation’s youth and the future workforce with fundamental knowledge of AI. Informal settings, such as museums, offer open and flexible opportunities in helping youth and the general public learn about AI. Virtual Humans provide an ideal vehicle to illustrate many fields of AI, as AI is arguably the science of building intelligence that thinks and acts like humans. Led by a multidisciplinary team of researchers with expertise in AI, learning design, and assessment from the Institute for Creative Technologies at University of Southern California and the Lawrence Hall of Science at University of California, Berkeley, this project will develop a Virtual Human exhibit to engage visitors through structured conversations with a Virtual Human, while showcasing how AI drives the Virtual Human’s behavior behind the scenes. The exhibit will include collaborative learning experiences for visitors such as parent-child, siblings and peers to explore what AI is and is not, what AI is and is not capable of, and what impact it will have on their lives.
The project will investigate three research questions: (1) How can a museum exhibit be designed to engage visitor dyads in collaborative learning about AI? (2) How can complex AI concepts underlying the Virtual Human be communicated in a way that is understandable by the general public? And (3) How does and to what extent the Virtual Human exhibit increase knowledge and reduce misconceptions about AI?
The project leverages existing conversational Virtual Human technology developed through decades of collaborative research in AI, including machine vision, natural language processing, automated reasoning, character animation, and machine learning. Set in the informal setting of a museum, the exhibit will be designed following evidence-based research in Computer Supported Collaborative Learning. The project team will use a mixed methods design, drawing on design-based research methodologies and experimental studies. The research team will conduct analysis of visitor observations and interviews for iterative formative improvement. Randomized experimental studies will be conducted in both lab and naturalistic environments to gauge visitor knowledge about AI. Quasi-experimental analyses will be performed to study the relationship between engagement with exhibit features and AI knowledge. The project will produce an interactive exhibit with a Virtual Human installed at the Lawrence Hall of Science and other participating museums, and instruments to measure AI learning. The project will also produce a website where visitors can experience parts of the exhibit online and continue more in-depth learning about AI and the Virtual Human technology. The project holds the potential for producing theoretical and practical advances in helping the general public develop an understanding of AI capability and ethics, advancing knowledge in the process through which young learners develop knowledge about AI, and formulating design principles for creating collaborative learning experiences in informal settings. The results will be disseminated through conference presentations, scholarly publications, and social media. The Virtual Human exhibit will be designed for dissemination and made available for installations at informal science education communities.