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
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?
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TEAM MEMBERS:
Ross Higashi
resourceprojectProfessional Development, Conferences, and Networks
Aligning for Impact: Computer Science Pathways Across Contexts [CS-PAC] is an NSF INCLUDES Design and Development Launch Pilot. It broadens participation of students who are underrepresented in computer science by using the convening and policy-making power of the Georgia State Department of Education to coalesce school district leaders to implement K-12 computer science education. The project provides a national model for how to work toward systemic change. With the State Department of Education's coordination, several school districts will collaboratively seek improvements in their own student participation rates. The coordination of data reporting and analysis, resources, communications, and policy promote more equitable participation in computer science education. Research emerging from this project informs other states about how to collaboratively shape computer science education policy and policy implementation.
Using a Collective Impact approach to systemic change, the project creates sustainable institutional change at the community, state, and national levels. Qualitative and quantitative data provide descriptions about how to utilize alignment strategies within Collective Impact in three different contexts: rural, suburban, and urban. Outcomes utilize a regression discontinuity analysis to justify successful implementation as well as qualitative analysis of implementation efforts that were deemed most effective by all stakeholders. The project outputs directly affect over 88,000 students across five districts and indirectly affect over 1.7 million in Georgia alone. The culminating project goal is the development of a coherent framework for aligning K-12 computer science education pathways.
Cities and communities in the U.S. and around the world are entering a new era of transformational change, in which their inhabitants and the surrounding built and natural environments are increasingly connected by smart technologies, leading to new opportunities for innovation, improved services, and enhanced quality of life. The Smart and Connected Communities (SCC) program supports strongly interdisciplinary, integrative research and research capacity-building activities that will improve understanding of smart and connected communities and lead to discoveries that enable sustainable change to enhance community functioning. This project is a Research Coordination Network (RCN) that focuses on achieving SCC for medium/small size, remote, and rural communities through a polycentric (multiple centers) integrated policy, design, and technology approach. The communities served by the RCN have higher barriers to information, resources, and services than larger urban communities. To reduce this gap, the PIs propose to develop need-based R&D pipelines to select solutions with the highest potential impacts to the communities. Instead of trying to connect under-connected communities to nearby large cities, this proposal aims to develop economic opportunities within the communities themselves. This topic aligns well with the vision of the SCC program, and the proposed RCN consists of a diverse group of researchers, communities, industry, government, and non-profit partners.
This award will support the development of an RCN within the Commonwealth of Virginia which will coordinate multiple partners in developing innovations utilizing smart and connected technologies. The goal of the research coordination network is to enable researchers and citizens to collaborate on research supporting enhanced quality of life for medium, small, and rural communities which frequently lack the communication and other infrastructure available in cities. The research coordination network will be led by the University of Virginia. There are 14 partner organizations including six research center partners in transportation, environment, architecture and urban planning, and engineering and technology; two State and Industry partners (Virginia Municipal League and Virginia Center for Innovative Technology); four community partners representing health services (UVA Center for Telemedicine), small and remote communities (Weldon Cooper Center), neighborhood communities (Charlottesville Neighborhood Development), and urban communities (Thriving Cities); and two national partners which support high speed networking (US-Ignite) and city-university hubs (MetroLab). Examples of research coordination include telemedicine services, transportation services, and user-centric and community-centric utilization and deployment of sensor technologies.
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TEAM MEMBERS:
Ila BermanT. Donna ChenKaren RheubanQian Cai
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 Research in Service to Practice project will address the issues around Informal Education of rural middle school students who have high potential regarding academic success in efforts to promote computer and IT knowledge, advanced quantitative knowledge, and STEM skills. Ten school districts in rural Iowa will be chosen for this study. It is anticipated that new knowledge on rural informal education will be generated to benefit the Nation's workforce. The specific objectives are to understand how informal STEM learning shapes the academic and psychosocial outcomes of rural, high-potential students, and to identify key characteristics of successful informal STEM learning environments for rural, high-potential students and their teachers. The results of this project will provide new tools for educators to increase the flow of underserved students into STEM from economically-disadvantaged rural settings.
The President's Council of Advisors on Science and Technology predicts a rapid rise in the number of STEM jobs available in the next decade, describing an urgent need for students' educational opportunities to prepare them for this workforce. In 2014, 62% of CEOs of major US corporations reported challenges filling positions requiring advanced computer and information technology knowledge. The project team will use a mixed methods approach, integrating comparative case study and mixed effects longitudinal methods, to study the Excellence program. Data sources include teacher interviews, classroom observations, and student assessments of academic aptitude and psychosocial outcomes. The analysis and evaluation of the program will be grounded in understanding the local efforts of school districts to build curriculum responsive to the demands of their high-potential student body. The project design, and subsequent analysis plan, utilizes a mixed methods approach, incorporating case study and longitudinal quantitative methods to analyze naturalistic data and build robust evidence for the implementation and impact of this program. This project will provide significant insights in how best to design, implement, and support informal out-of-school learning environments to broaden participation in the highest levels of STEM education and careers for under-resourced rural students.
While the term 'failure' brings to mind negative associations, there is a current focus on failure as a driver of innovation and development in many professional fields. It is also emerging from prior research that for STEM professionals and educators, failure plays an important role in designing and making to increase learning, persistence and other noncognitive skills such as self-efficacy and independence. By investigating how youth and educators attend to moments of failure, how they interpret what this means, and how they respond, we will be better able to understand the dynamics of each part of the experience. The research team will be working with youth from urban, suburban and rural settings, students from Title I schools or who qualify for free/reduced-price lunches, those from racial and ethnic minority groups, as well as students who are learning English as a second language. These youth are from groups traditionally underrepresented in STEM and in making, and research indicates they are more likely to experience negative outcomes when they experience failure.
The intellectual merit of this project centers on establishing a baseline understanding of how failure in making is triggered and experienced by youth, what role educators play in the process, and what can be done to increase persistence and learning, rather than failure being an end-state. The research team will investigate these issues through the use of qualitative and quantitative research methods. In particular, the team will design and evaluate the effectiveness of interventions on increasing the abilities of youth and educators in noticing and responding to failures and increasing positive (e.g., resilience) outcomes. Research sites are selected because they will allow collection of data on youth from a wide range of backgrounds. The research team will also work to test and revise their hypothesized model of the influence of factors on persistence through failures in making. This project is a part of NSF's Maker Dear Colleague Letter (DCL) portfolio (NSF 15-086), a collaborative investment of Directorates for Computer & Information Science & Engineering (CISE), Education and Human Resources (EHR) and Engineering (ENG).