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
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
Research that seeks to understand classroom interactions often relies on video recordings of classrooms so that researchers can document and analyze what teachers and students are doing in the learning environment. When studies are large scale, this analysis is challenging in part because it is time-consuming to review and code large quantities of video. For example, hundreds of hours of videotaped interaction between students working in an after-school program for advancing computational thinking and engineering learning for Latino/a students. This project is exploring the use of computer-assisted methods for video analysis to support manual coding by researchers. The project is adapting procedures used for computer-aided diagnosis systems for medical systems. The computer-assisted process creates summaries that can then be used by researchers to identify critical events and to describe patterns of activities in the classroom such as students talking to each other or writing during a small group project. Creating the summaries requires analyzing video for facial recognition, motion, color and object identification. The project will investigate what parts of student participation and teaching can be analyzed using computer-assisted video analysis. This project is supported by NSF's EHR Core Research (ECR) program, the STEM+C program and the AISL program. The ECR program emphasizes fundamental STEM education research that generates foundational knowledge in the field. The project is funded by the STEM+Computing program, which seeks to address emerging challenges in computational STEM areas through the applied integration of computational thinking and computing activities within disciplinary STEM teaching and learning in early childhood education through high school (preK-12). 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.
The video analysis systems will provide video summarizations for specific activities which will allow researchers to use these results to quantify student participation and document teaching practices that support student learning. This will support the analysis of large volumes of video data that are often time-consuming to analyze. The video analysis system will identify objects in the scene and then use measures of distances between objects and other tracking methods to code different activities (e.g., typing, talking, interaction between the student and a facilitator). The two groups of research questions are as follows. (1) How can human review of digital videos benefit from computer-assisted video analysis methods? Which aspects of video summarization (e.g., detected activities) can help reduce the time it takes to review the videos? Beyond audio analytics, what types of future research in video summarization can help reduce the time that it takes to review videos? (2) How can we quantify student participation using computer-assisted video analysis methods? What aspects of student participation can be accurately measures by computer-assisted video analysis methods? The video to be used for this study is drawn from a project focused on engineering and computational thinking learning for Latino/a students in an after-school setting. Hundreds of hours of video are available to be reviewed and analyzed to design and refine the system. The resulting coding will also help document patterns of engagement in the learning environment.
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:
Marios PattichisSylvia Celedon-PattichisCarlos LopezLeiva
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 “Fourth Industrial Revolution” is transforming the world of work. Just as it happened with the technologies of the steam, electricity and computer revolutions, digital technologies are now becoming pervasive and reshaping all parts of the global economy. The computing industry’s rate of job creation in the U.S. is now three times the U.S. national average. This rapid expansion of the computing workforce means that computing skills – with coding at the core – are the most sought-after skills in the American job market.
Yet amid this boom, research by Accenture and Girls Who Code shows
Computer science education is rapidly being recognized as essential for all students to develop into successful citizens of the 21st century. A diverse group of stakeholders, including educators, business and industry, policymakers, and parents all agree on the importance of computer science. Significant workforce needs in particular are driving the push for computer science education. In comparison to all other U.S. job categories, computing is projected to have the largest percent growth between 2014 and 2024. And this projected growth may not even entirely capture the full number of
This is an Early-concept Grant for Exploratory Research supporting research in Smart and Connected Communities. The research supported by the award is collaborative with research at the University of Colorado. The researchers are studying the use of technologies to enable communities to connect youth and youth organizations to effectively support diverse learning pathways for all students. These communities, the youth, the youth organizations, formal and informal education organizations, and civic organizations form a learning ecology. The DePaul University researchers will design and implement a smart community infrastructure in the City of Chicago to track real-time student participation in community STEM activities and to develop mobile applications for both students and adults. The smart community infrastructure will bring together information from a variety of sources that affect students' participation in community activities. These include geographic information (e.g., where the student lives, where the activities take place, the student transportation options, the school the student attends), student related information (e.g., the education and experience background of the student, the economic status of the student, students' schedules), and activity information (e.g., location of activity, requirements for participation). The University of Colorado researchers will take the lead on analyzing these data in terms of a community learning ecologies framework and will explore computational approaches (i.e., recommender systems, visualizations of learning opportunities) to improve youth exploration and uptake of interests and programs. These smart technologies are then used to reduce the friction in the learning connection infrastructure (called L3 for informal, formal, and virtual learning) to enable the student to access opportunities for participation in STEM activities that are most feasible and most appropriate for the student. Such a flexible computational approach is needed to support the necessary diversity of potential recommendations: new interests for youth to explore; specific programs based on interests, friends' activities, or geographic accessibility; or programs needed to "level-up" (develop deeper skills) and complete skills to enhance youths' learning portfolios. Although this information was always available, it was never integrated so it could be used to serve the community of both learners and the providers and to provide measurable student learning and participation outcomes. The learning ecologies theoretical framework and supporting computational methods are a contribution to the state of the art in studying afterschool learning opportunities. While the concept of learning ecologies is not new, to date, no one has offered such a systematic and theoretically-grounded portfolio of measures for characterizing the health and resilience of STEM learning ecologies at multiple scales. The theoretical frameworks and concepts draw together multiple research and application domains: computer science, sociology of education, complexity science, and urban planning. The L3 Connects infrastructure itself represents an unprecedented opportunities for conducting "living lab" experiments to improve stakeholder experience of linking providers to a single network and linking youth to more expanded and varied opportunities. The University of Colorado team will employ three methods: mapping, modeling, and linking youth to STEM learning opportunities in school and out of school settings in a large urban city (Chicago). The recommender system will be embedded into youth and parent facing mobile apps, enabling the team to characterize the degree to which content-based, collaborative filtering, or constraint based recommendations influence youth actions. The project will result in two measurable outcomes of importance to key L3 stakeholder groups: a 10% increase in the number of providers (programs that are part of the infrastructure) in target neighborhoods and a 20% increase in the number of youth participating in programs.
This is an Early-concept Grant for Exploratory Research supporting research in Smart and Connected Communities. The research supported by the award is collaborative with research at DePaul University. The researchers are studying the use of technologies to enable communities to connect youth and youth organizations to effectively support diverse learning pathways for all students. These communities, the youth, the youth organizations, formal and informal education organizations, and civic organizations form a learning ecology. The DePaul University researchers will design and implement a smart community infrastructure in the City of Chicago to track real-time student participation in community STEM activities and to develop mobile applications for both students and adults. The smart community infrastructure will bring together information from a variety of sources that affect students' participation in community activities. These include geographic information (e.g., where the student lives, where the activities take place, the student transportation options, the school the student attends), student related information (e.g., the education and experience background of the student, the economic status of the student, students' schedules), and activity information (e.g., location of activity, requirements for participation). The University of Colorado researchers will take the lead on analyzing these data in terms of a community learning ecologies framework and will explore computational approaches (i.e., recommender systems, visualizations of learning opportunities) to improve youth exploration and uptake of interests and programs. These smart technologies are then used to reduce the friction in the learning connection infrastructure (called L3 for informal, formal, and virtual learning) to enable the student to access opportunities for participation in STEM activities that are most feasible and most appropriate for the student. Such a flexible computational approach is needed to support the necessary diversity of potential recommendations: new interests for youth to explore; specific programs based on interests, friends' activities, or geographic accessibility; or programs needed to "level-up" (develop deeper skills) and complete skills to enhance youths' learning portfolios. Although this information was always available, it was never integrated so it could be used to serve the community of both learners and the providers and to provide measurable student learning and participation outcomes. The learning ecologies theoretical framework and supporting computational methods are a contribution to the state of the art in studying afterschool learning opportunities. While the concept of learning ecologies is not new, to date, no one has offered such a systematic and theoretically-grounded portfolio of measures for characterizing the health and resilience of STEM learning ecologies at multiple scales. The theoretical frameworks and concepts draw together multiple research and application domains: computer science, sociology of education, complexity science, and urban planning. The L3 Connects infrastructure itself represents an unprecedented opportunities for conducting "living lab" experiments to improve stakeholder experience of linking providers to a single network and linking youth to more expanded and varied opportunities. The University of Colorado team will employ three methods: mapping, modeling, and linking youth to STEM learning opportunities in school and out of school settings in a large urban city (Chicago). The recommender system will be embedded into youth and parent facing mobile apps, enabling the team to characterize the degree to which content-based, collaborative filtering, or constraint based recommendations influence youth actions. The project will result in two measurable outcomes of importance to key L3 stakeholder groups: a 10% increase in the number of providers (programs that are part of the infrastructure) in target neighborhoods and a 20% increase in the number of youth participating in programs.
This Research in Service to Practice project, a collaboration of Pepperdine University and the New York Hall of Science, will establish a network of STEM-related Media Making Clubs comprised of after-school students aged 12 - 19 and teachers in the U.S. and in three other countries: Kenya, Namibia and Finland. The media produced by the students may include a range of formats such as videos, short subject films, games, computer programs and specialized applications like interactive books. The content of the media produced by the students will focus on the illustration and teaching of STEM topics, where the shared media is intended to help other students become enthused about and learn the science. This proposal builds on the principal investigator's previous work on localized media clubs by now creating an international network in which after-school students and teachers will collaborate at a distance with other clubs. The central research questions for the project pertain to three themes at the intersection of learning, culture and collaboration: the impact of participatory teaching, virtual networks, and intercultural, global competence. The research will combine qualitative, cross-cultural and big data methods. Critical to the innovation of the project, the research team will also develop a network assessment tool, adapting epistemic network analysis methods to the needs of this initiative. This work 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.
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TEAM MEMBERS:
Eric HamiltonKatherine McMillanPriya Mohabir
Situated within the Advancing Informal STEM Learning program, this Research in Service to Practice award seeks to design, implement, and evaluate an intervention aimed at fostering a culture of productive failure practices. The project responds to a broad concern in educational research and practice: Experiences of failure are frequently so negative that students shut down, lose agency, and develop low self-efficacy and learned helplessness. Surrendering too quickly to obstacles is particularly unfortunate, given evidence that initially "getting it wrong" ultimately breeds deep and sustained learning. In order to learn how students can make the most of productive failure, the proposed project will study how a community of practice that includes middle school youth and their mentors attempts to change its handling of learning obstacles. Building on prior research documenting storytelling practices in an afterschool program, the team now aims to embolden young students' productive practices of failure storytelling in computer science, a field in which experts practice candid, pervasive, and collaborative discourse around errors ("bugs"). Pulling together the domains of narrative analysis, meta-cognitive reflection, and control theories of motivation, within the context of authentic computer-science debugging activity, this study develops a theoretical framework that views productive responses to failure as a discipline-specific process of reflecting as a community on how to locate obstacles, how to construct causal theories about why those obstacles emerged, and how to plan productive responses. A design-based research approach will investigate three questions: (1) What is the impact of the interventions on students and instructors' actions and discourse when they are debugging errors in computer code? (2) What is the impact of the interventions on students and instructors' reflections back on their prior debugging experiences and on failure in general? and (3) What is the impact of the instructor-development efforts on the instructors' capacity to foster students' productive attitudes toward failure? The study focus will be 15 summer and weekend coding workshops with 5th-8th grade students from populations typically under-represented in STEM. The interventions are (a) setting new norms and practices for debugging, (b) instructor education, and (c) coding software that provides students with feedback on their productive struggle. Data sources include video and audio recordings of the learning environment, artifacts produced during the activities, and semi-structured interviews. Measures will capture variations in debugging activities, reflections on debugging, students' ideas about grit and growth mindset, and instructors' struggles and successes with the new curriculum. The empirical results will consist of mixed-methods, micro-longitudinal accounts of how a community of practice works to reform its orientation to failure. The products of this work include empirical knowledge, theory, and curriculum about how learning communities help students develop robust and efficient responses to failure. These will be disseminated through journals, open-source software, and workshops/conferences for researchers and practitioners working with youth afterschool programs. The products may be useful for exploring practices in the classroom. This project is being conducted by the 9 Dots Community Learning Center, UCLA and UC Berkeley.
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TEAM MEMBERS:
Melissa ChenDor AbrahamsonNoel EnyedyFrancis SteenDavid DeLiema