This paper attempts to reframe popular notions of “failure” as recently celebrated in the Maker Movement, Silicon Valley, and beyond. Building on Vossoughi et al.’s 2013 FabLearn publication describing how a focus on iterations/drafts can serve as an equity-oriented pedagogical move in afterschool tinkering contexts, we explore what it means for afterschool youth and educators to persist through unexpected challenges when using an iterative design process in their tinkering projects. More specifically, this paper describes: 1) how young women in a program geared toward increasing equitable
Artificial Intelligence (AI), the research and development of machines to mimic human thought and behavior, encompasses one of the most complex scientific and engineering challenges in history. AI now permeates essentially all sectors of the economy and society. Young people growing up in the era of big data, algorithms, and AI need to develop new awareness, content knowledge, and skills to understand humans’ relationships with these new technologies and become producers of AI artifacts themselves.
YR Media and MIT’s Understanding AI project researched and developed innovative approaches to
This poster was presented at the 2021 NSF AISL Awardee Meeting.
Makerspaces and making-related programs are often inaccessible, unaffordable, or simply not available to underserved youth. This three-year, Innovations in Development project involves partnership with four Recreation Centers (two each in Baltimore and Pittsburgh) to (1) train educators in equity-oriented approaches to making, (2) create four learning hubs, (3) develop and test equity-based curricula in each space, and (4) establish a replicable Localization Toolkit for future implementation in other communities.
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?
This project will teach foundational computational thinking (CT) concepts to preschoolers by creating a series of mobile apps to guide families through sequenced sets of videos and hands-on activities. To support families at home it would also develop a new library model to build librarians' computational thinking content knowledge and self-efficacy so they can support parents' efforts with their children. Computational thinking is a an increasingly critical skill for learning and success in the workforce. It includes the ability to identify problems, brainstorm and generate solutions and processes that can be communicated and followed by computers or humans. There are few projects that introduce computational thinking to young children. Very little research has been done on the ways that parents can facilitate children's engagement in CT skills. And developing a model that trains and supports librarians to become virtual coaches of parents as they engage with their children in CT, will leverage and build the expertise of librarians. The project's target audience includes parents and children living in rural areas where access to CT learning may be very limited. Project partners include the EDC, a major research organization, the American Library Association, and BUILD, a national association that promotes collaborations across library, kindergarten readiness, and public media programming.
The formative research study asks: 1) What supports do parents of preschoolers in rural communities need in order to effectively engage in CT with their children at home? and 2) How can libraries in rural communities support joint CT exploration in family homes? The summative research study asks: 3) how can an intervention that combines media resources, mobile technology, and library supports foster sustained joint parent/child engagement and positive attitudes around CT? Researchers will develop a parent survey, adapting several scales from previously developed instruments that ask parents to report on children's use of CT-related vocabulary and CT-related attitudes and dispositions. Survey scales will assess librarians' attitudes towards CT, as well as their self-efficacy in supporting parents in CT in a virtual environment. During the formative study, EDC will pilot-test survey scales with 30 parents and 6 librarians in rural MS and KY. Analyses will be primarily qualitative and will be geared toward producing rapid feedback for the development team. Quantitative analyses will be used on parent app use, using both time query and back-end data, exploring factors associated with time spent using apps. The summative study will evaluate how the new media resources and mobile technology, in combination with the library virtual implementation model, support families' joint engagement with CT, and positive attitudes around CT. The researchers will recruit 125 low-income families with 4- to 5-year-old children in rural MS and KY to participate in the study. They will randomly assign families within each library to the full intervention condition, including media resources, mobile technology, and library support delivered through the virtual implementation model, or the media and mobile-technology-only condition. This design will allow researchers to understand more fully the additional benefit of library support for rural families' sustained engagement, and conversely, see the comparative impact of a media- and mobile-technology only intervention, given that some families might not be able to access virtual or physical library support.
As part of its overall strategy to enhance learning in informal environments, the Advancing Informal STEM Learning (AISL) program seeks to advance new approaches to, and evidence-based understanding of, the design and development of STEM learning in informal environments. This includes providing multiple pathways for broadening access to and engagement in STEM learning experiences, advancing innovative research on and assessment of STEM learning in informal environments, and developing understandings of deeper learning by participants. This project is co-funded by the Innovative Technology Experiences for Students and Teachers (ITEST) program, which supports projects that build understandings of practices, program elements, contexts and processes contributing to increasing students' knowledge and interest in science, technology, engineering, and mathematics (STEM) and information and communication technology (ICT) careers.
This Innovations in Development award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Refugee youth are particularly vulnerable to STEM disenfranchisement due to factors including limited or interrupted schooling following displacement; restricted exposure to STEM education; and linguistic, cultural, ethnic, socioeconomic, and racial minority status. Refugee youth may experience a gap in STEM skills and knowledge, and a conflict between the identities necessary for participation in their families and communities, and those expected for success in STEM settings. To conduct research to better understand these challenges, an interrelated set of activities will be developed. First, youth will learn principles of physics and computing by participating in cosmic ray research with physicists using an instructional approach that builds from their home languages and cultures. Then youth periodically share what they are learning in the cosmic ray research with their parents, siblings, and science teachers at family and community science events. Finally, youth conduct reflective research on their own STEM identity development over the course of the project. Research on learning will be conducted within and across these three strands to better understand how refugee youth develop STEM-positive identities. This project will benefit society by improving equity and diversity in STEM through (1) creating opportunities for refugee youth to participate in physics research and to develop computing skills and (2) producing knowledge on STEM identity development that may be applied more broadly to improve STEM education. Deliverables from this project include: (a) research publications on STEM identity and learning; (b) curriculum resources for teaching physics and computing to multilingual youth; (c) an online digital storytelling exhibit offering narratives about belonging in STEM research which can be shared with STEM stakeholders (policy makers, scientists, educators, etc.); and (d) an online database of cosmic ray data which will be available to physicists worldwide for research purposes. This Innovations in Development proposal 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. This includes providing multiple pathways for broadening access to and engagement in STEM learning experiences, advancing innovative research on and assessment of STEM learning in informal environments, and developing understandings of deeper learning by participants.
This program is designed to provide multiple contexts, relationships, and modes across and within which the identity work of individual students can be studied to look for convergence or divergence. To achieve this goal, the research applies a linguistic anthropological framework embedding discourse analysis in a larger ethnography. Data collected in this study include field notes, audio and video recordings of naturalistic interactions in the cosmic ray research and other program activities, multimodal artifacts (e.g., students' digital stories), student work products, interviews, and surveys. Critically, this methodology combines the analysis of identity formation as it unfolds in moment-to-moment conversations (during STEM learning, and in conversations about STEM and STEM learning) with reflective tasks and the production of personal narratives (e.g., in digital stories and interviews). Documenting convergence and divergence of STEM identities across these sources of data offers both methodological and theoretical contributions to the field. The research will offer thick description of the discursive practices of refugee youth to reveal how they construct identities related to STEM and STEM disciplines across settings (e.g., during cosmic ray research, while creating digital stories), relationships (e.g., peer, parent, teacher), and the languages they speak (e.g., English, Swahili). The findings will be of potential value to instructional designers of informal learning experiences including those working with afterschool, museums, science centers and the like, educators, and scholars of learning and identity.
This Innovations in Development award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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TEAM MEMBERS:
Tino NyaweloJohn MatthewsJordan GertonSarah Braden
This award takes an innovative approach to an ongoing, pervasive, and persistent societal issue: women are still drastically underrepresented in computing careers. This project targets middle school-aged girls because it is a time when many of them lose interest and confidence in pursuing technical education and computing careers. This project will design, develop, and deploy a one-week experience focused on middle school girls that targets this issue with a novel combination of teaching techniques and technology. The project will use wearable computing devices to support girls' social interactions as they learn computing and solve technical challenges together. The goals of the project are to raise interest, perceived competence, and involvement in the computational ability of girls. Additionally, the project aims to increase a sense of computational community for girls that makes pursuing computational skills more relevant to their identities and lives, and that helps continued participation in computing. The project will deploy a one-week experience four times per year with a socioeconomically diverse range of campers. The project will also develop a 'program in a box' kit that can be broadly used by others wishing to deliver a similar experience for girls.
The planned research will determine if a one-week experience that uses social wearable construction in the context of live-action role play can use the mediating process of computational community formation to positively impact middle school girls' engagement with and interest in computation. Computational community is defined as girls engaging together in the process of learning computation, trading resources and knowledge, and supporting growth. Research participants will include 100 6th to 9th-grade girls. At least 75% of the participants will be either low income, first-generation college-bound, or underrepresented in higher education. Students will be recruited through the longstanding partnerships with title one schools in the Salinas Valley, the Educational Partnership Center, and in the Pajaro Valley Unified School district, where 82% of the students are Hispanic/Latinx, 42% are English Learners, and 73% are eligible for free or reduced lunch. The research questions are: 1) Does the proposed experience increase girls' self-reported competence, self-efficacy, and interest in computational skills and careers? and 2) Will the proposed experience lead to activity-based evidence of learning and integration of computational skills at the group social level? The project will use a mixed-methods, design-based research approach which is an iterative design process to rapidly collect and analyze data, and regularly discuss the implications for practice with the design team. Data will be collected using observations, interviews, focus groups, surveys, and staff logs. Quantitative data will be analyzed using frequencies, means, and measures of dispersion will be applied to survey data from both time points. Pearson correlation coefficients will be used to describe the bivariate relationship between continuous factors. ANOVAs will assess whether there are significant differences in continuous measures across groups. Qualitative data will be analyzed using a constant comparison method.
This Innovations in Development award 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. This includes providing multiple pathways for broadening access to and engagement in STEM learning experiences.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
We explored the potential of science to facilitate social inclusion with teenagers who had interrupted their studies before the terms set for compulsory education. The project was carried out from 2014 to 2018 within SISSA (International School for Advanced Studies), a scientific and higher education institution in physics, mathematics and neurosciences, and was focused on the production of video games using Scratch. The outcomes are encouraging: through active engagement, the participants have succeeded in completing complex projects, taking responsibilities and interacting with people
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TEAM MEMBERS:
Simona CerratoFrancesca RizzatoLucia TealdiElena Canel
This paper contributes a theoretical framework informed by historical, philosophical and ethnographic studies of science practice to argue that data should be considered to be actively produced, rather than passively collected. We further argue that traditional school science laboratory investigations misconstrue the nature of data and overly constrain student agency in their production. We use our “Data Production” framework to analyze activity of and interviews with high school students who created data using sensors and software in a ninth-grade integrated science class. To understand the
Despite the ubiquity of Artificial Intelligence (AI), public understanding of how it works and is used is limited This project will research, design, and develop innovative approaches focusing on Artificial Intelligence (AI) for under-represented youth ages 14-24. Program components include live social media chats with AI leaders, app development, journalistic investigations of ethical issues in machine learning, and review of AI-based consumer products. Youth Radio is a non-profit media and tech organizations that provides youth with skills in STEM, journalism, arts, and communications. They engage 250 youth annually through free after-school classes and work shifts. Participants are 90% youth of color and 80% low income. Project partners include the MIT Media Lab which developed App Inventor which allows novice users to build fully functional apps. Staff from Google will serve as a project advisor on the curriculum. The project has exceptional national reach through the dissemination of its media and apps through national outlets such as NPR and Teen Vogue as well as various platforms including online, on-air, as well as presentations, publications, and training tools. The project broadens participation by engaging these low income youth of color in developing skills critical to the workforce of the future. It will help prepare an upcoming generation of Artificial Intelligence creators, users, and consumers who understand the technology and embrace and encourage its potential.It will give them the necessary knowledge and opportunities for careers in an AI-driven future.
This project is grounded in sociocultural learning theory and practice and is interdisciplinary by design. The theoretical framework holds that Computational Thinking plus Critical Pedagogy leads to Critical Computational Literacy. Also, Digital Age Civics plus Participatory Culture leads to Civic Imagination helping youth build a better world through technology. The driving research questions include: What do underrepresented youth understand about AI and its role in society? What are the ethical dilemmas posed by AI from their vantage point? What are the features of an engaging ethics-centered pedagogy with AI? What impact do the AI products developed by the youth have on the target audience? The research design will use ethnographic techniques and design research to study and analyze youth learning. Data sources will include baseline surveys, audio recordings and transcriptions from learning sessions with the participants, research analytic memos, focus group interviews, student-generating artifacts of learning and finished products, etc. The design-based approach will enable systematic, evidence-based iteration on the initiative's activities, pedagogical approach and products. An independent summative evaluation will provide complementary data and perspective to triangulate with the research findings.
This project is funded by the National Science Foundation's (NSF's) Advancing Informal STEM Learning (AISL) program, which supports innovative research, approaches, and resources for use in a variety of learning settings.
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TEAM MEMBERS:
Elisabeth SoepEllin O'LearyHarold Abelson
This one-year Collaborative Planning project seeks to bring together an interdisciplinary planning team of informal and formal STEM educators, researchers, scientists, community, and policy experts to identify the elements, activities, and community relationships necessary to cultivate and sustain a thriving regional early childhood (ages 3-6) STEM ecosystem. Based in Southeast San Diego, planning and research will focus on understanding the needs and interests of young Latino dual language learners from low income homes, as well as identify regional assets (e.g., museums, afterschool programs, universities, schools) that could coalesce efforts to systematically increase access to developmentally appropriate informal STEM activities and resources, particularly those focused on engineering and computational thinking. This project has the potential to enhance the infrastructure of early STEM education by providing a model for the planning and development of early childhood focused coalitions around the topic of STEM learning and engagement. In addition, identifying how to bridge STEM learning experiences between home, pre-k learning environments, and formal school addresses a longstanding challenge of sustaining STEM skills as young children transition between environments. The planning process will use an iterative mixed-methods approach to develop both qualitative and quantitative and data. Specific planning strategies include the use of group facilitation techniques such as World Café, graphic recording, and live polling. Planning outcomes include: 1) a literature review on STEM ecosystems; 2) an Early Childhood STEM Community Asset Map of southeast San Diego; 3) a set of proposed design principles for identifying and creating early childhood STEM ecosystems in low income communities; and 4) a theory of action that could guide future design and research. This project is funded by the Advancing Informal STEM Learning program, which seeks to advance new approaches to, and evidence-based understanding of, the design and development of STEM learning in informal environments.
The Colleges of Science & Engineering and Graduate Education, and the Metro Academies College Success Program (Metro) at San Francisco State University in partnership with San Francisco Unified School District and the San Francisco Chamber of Commerce develop an integrated approach for computing education that overcomes obstacles hampering broader participation in the U.S. science, technology, engineering and mathematics (STEM) workforce. The partnership fosters a more diverse and computing-proficient STEM workforce by establishing an inclusive education approach in computer science (CS), information technology, and computer engineering that keeps students at all levels engaged and successful in computing and graduates them STEM career-ready.
Utilizing the collective impact framework maximizes the efficacy of existing regional organizations to broaden participation of groups under-educated in computing. The collective impact model establishes a rich context for organizational engagement in inclusive teaching and learning of CS. The combination of the collective impact model of social agency and direct engagements with communities yields unique insights into the views and experiences of the target population of students and serves as a platform for national scalable networks.
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TEAM MEMBERS:
Keith BowmanIlmi YoonLarry HorvathEric HsuJames Ryan