Informal STEM learning experiences (ISLEs), such as participating in science, computing, and engineering clubs and camps, have been associated with the development of youth’s science, technology, engineering, and mathematics interests and career aspirations. However, research on ISLEs predominantly focuses on institutional settings such as museums and science centers, which are often discursively inaccessible to youth who identify with minoritized demographic groups. Using latent class analysis, we identify five general profiles (i.e., classes) of childhood participation in ISLEs from data
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TEAM MEMBERS:
Remy DouHeidi CianZahra HazariPhilip SadlerGerhard Sonnert
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
Data is increasingly important in all aspects of people’s lives, from the day-to-day, to careers and to civic engagement. Preparing youth to use data to answer questions and solve problems empowers them to participate in society as informed citizens and opens doors to 21st century career opportunities. Ensuring equitable representation in data literacy and data science careers is critical. For many girls underrepresented in STEM, developing a "data science identity" requires personally meaningful experiences working with data. This project aims to promote middle school-aged girls’ interest and aspirations in data science through an identity-aligned, social game-based learning approach. The goals are to create a more diverse and inclusive generation of data scientists who see data as a resource and who are equipped with the skills and dispositions necessary to work with data in order to solve practical problems. The research team will run 10 social clubs and 10 data science clubs mentored by women in data science recruited through the University of Miami’s Institute for Data Science and Computing. Participants will be 250 middle school-aged girls recruited in Miami, FL, and Yolo County, CA, through local and national girls’ organizations. Youth will participate in a data science club and will learn key data science concepts and skills, including data structures, storage, exploration, analysis, and visualization. These concepts will be learned from working with their own data collected in personally meaningful ways in addition to working with data collected by others in the same social game eco-system. The project will also develop facilitator materials to allow adult volunteers to create game-based informal data science learning experiences for youth in their areas. 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 and is co-funded by the Innovative Technology Experiences for Students and Teachers (ITEST), which seeks to engage underrepresented students in technology-rich learning environments, including skills in data literacy, and increase students’ knowledge and interest in information and communication technology (ICT) careers.
Researchers will focus on two primary research questions: 1) Across gameplay and club experiences, in what ways do participants engage with data to pursue personal or social goals? 2) How do gameplay and club experiences shape girls’ perceptions of data, data science, and their fit with data and data science? The project will use design-based research methods to iteratively design the game and social club experiences. To ensure that uses of data feel personally and socially meaningful to young girls, the virtual world’s goals, narratives, and activities will be co-designed with girls from groups underrepresented in data science. The project will research engagement with game data in two informal, game-based learning scenarios: organic, self-directed, social play club, and structured, adult-facilitated data science clubs. The research will use a combination of quantitative and qualitative methods including surveys, focus groups, interviews, and gameplay and club observations. Project evaluation will determine how gameplay and club experiences impact participants' attitudes toward and interest in data-rich futures. The project holds the potential for broadening participation and promoting interest in data science by blending game-based learning with the rich social and adult mentoring through club participation. The results will be disseminated through conference presentations, scholarly publications, and social media. The game and facilitator materials will be designed for dissemination and made freely available to the public.
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TEAM MEMBERS:
Lisa HardyGary GoldbergerJennifer Kahn
This poster was presented at the 2021 NSF AISL Awardee Meeting.
Today’s young people have a personal stake in their ability to function with data. Future job prospects might hinge on their ability to participate in the new data economy. But equally, young people are themselves the subjects of data. The datafication of young people’s lives leads to profound questions about childhood, technology, and the equity of access to STEM learning around data, one of which is this: How might young people be empowered in a data-centric world?
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TEAM MEMBERS:
Leanne BowlerMark RosinIrene Lopatovska
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?
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