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.
DATE:
-
TEAM MEMBERS:
Marios PattichisSylvia Celedon-PattichisCarlos LopezLeiva
The Computational Thinking in Ecosystems (CT-E) project is funded by the STEM+Computing Partnership (STEM+C) program, which seeks to advance new approaches to, and evidence-based understanding of, the integration of computing in STEM teaching and learning. The project is a collaboration between the New York Hall of Science (NYSCI), Columbia University's Center for International Earth Science Information Network, and Design I/O. It will address the need for improved data, modeling and computational literacy in young people through development and testing of a portable, computer-based simulation of interactions that occur within ecosystems and between coupled natural and human systems; computational thinking skills are required to advance farther in the simulation. On a tablet computer at NYSCI, each participant will receive a set of virtual "cards" that require them to enter a computer command, routine or algorithm to control the behavior of animals within a simulated ecosystem. As participants explore the animals' simulated habitat, they will learn increasingly more complex strategies needed for the animal's survival, will use similar computational ideas and skills that ecologists use to model complex, dynamic ecological systems, and will respond to the effects of the ecosystem changes that they and other participants elicit through interaction with the simulated environment. Research on this approach to understanding interactions among species within biological systems through integration of computing has potential to advance knowledge. Researchers will study how simulations that are similar to popular collectable card game formats can improve computational thinking and better prepare STEM learners to take an interest in, and advance knowledge in, the field of environmental science as their academic and career aspirations evolve. The project will also design and develop a practical approach to programing complex models, and develop skills in communities of young people to exercise agency in learning about modeling and acting within complex systems; deepening learning in young people about how to work toward sustainable solutions, solve complex engineering problems and be better prepared to address the challenges of a complex, global society.
Computational Thinking in the Ecosystems (CT-E) will use a design-based study to prototype and test this novel, tablet-based collectable card game-like intervention to develop innovative practices in middle school science. Through this approach, some of the most significant challenges to teaching practice in the Next Generation Science Standards will be addressed, through infusing computational thinking into life science learning. CT-E will develop a tablet-based simulation representing six dynamic, interconnected ecosystems in which students control the behaviors of creatures to intervene in habitats to accomplish goals and respond to changes in the health of their habitat and the ecosystems of which they are a part. Behaviors of creatures in the simulation are controlled through the virtual collectable "cards", with each representing a computational process (such as sequences, loops, variables, conditionals and events). Gameplay involves individual players choosing a creature and habitat, formulating strategies and programming that creature with tactics in that habitat (such as finding food, digging in the ground, diverting water, or removing or planting vegetation) to navigate that habitat and survive. Habitats chosen by the participant are part of particular kinds of biomes (such as desert, rain forest, marshlands and plains) that have their own characteristic flora, fauna, and climate. Because the environments represent complex dynamic interconnected environmental models, participants are challenged to explore how these models work, and test hypotheses about how the environment will respond to their creature's interventions; but also to the creatures of other players, since multiple participants can collaborate or compete similar to commercially available collectable card games (e.g., Magic and Yu-Go-Oh!). NYSCI will conduct participatory design based research to determine impacts on structured and unstructured learning settings and whether it overcomes barriers to learning complex environmental science.
This report summarizes evaluative findings from Computational Thinking in Ecosystems project, and the resulting product, i.e., a functional draft of a game called “The Pack.” Evaluative efforts included gathering feedback from key stakeholders—including members of the design based research (DBR) team members at the New York Hall of Science (NYSCI) along with advisors and project partners— about the game and the DBR process, as well as an independent assessment of the game via feedback from educators and a round of play-testing with youth.
This project tackles the urgent needs of the nation to engage people of all ages in computational thinking and help them learn basic computer science concepts with a unique and innovative approach of structured in-game computer program coding. Researchers will explore the design and development of a 3D puzzle-based game, called May's Journey, in which players solve an environmental maze by using the game's pseudo code to manipulate game objects. The game is designed to teach introductory but foundational concepts of computer programming including abstraction, modularity, reusability, and debugging by focusing players on logic and concepts while asking them to type simple instructions in a simplified programming language designed for novices. The game design in this project differs from today's block-based programming learning approaches that are often too far from actual computer code, and also differs from professional programming languages which are too complex for novices. The game and its embedded programming language learning are designed to be responsive to the progress of the learner throughout the game, transitioning from pseudo code to the embedded programming language itself. Error messages for debugging are also designed to be adaptive to players' behavior in the game. Using extensive log data collected from people playing the game, researchers can study how people learn computer programming. Such knowledge can advance understanding of the learning processes in computer programming education. Additionally, this work emphasizes the use of games as informal learning environments as they are accessible and fun, drawing attention and retention of many learners of different age groups with the potential to change attitudes towards computer programming across different populations. This project is co-funded by the STEM + Computing (STEM+C) program that supports research and development to understand the integration of computing and computational thinking in STEM learning, and the Advancing Informal STEM Learning (AISL) program that funds innovative research, approaches and resources for use in a variety of settings with its overall strategy to enhance learning in informal environments.
The project's formative and summative evaluation methods, including surveys, expert reviews of learners' computer code developed in the game, and interviews, are used to gauge learners' engagement as well as learning. In exploring learning, researchers aim to understand how players build implicit computer science knowledge through gameplay and how that gameplay relates to their performance on external transfer tasks. The project will answer the following three research questions: (1) Can observers reliably detect and label patterns of gameplay that provide evidence of learning or misconceptions regarding the four computer science constructs - abstraction, modularity, debugging and semantics - that learners exhibit playing May's Journey? (2) How does learner's implicit knowledge of these computer science constructs change over time and do those patterns vary by gender and prior programming experiences? (3) Is there a strong correlation between implicit learning measures and transfer of CS concepts: modularity, debugging, semantics, and abstraction? How do these correlations vary across elements of the game? This work will result in several outcomes: game design metaphors tested for their learning and engagement value that can be abstracted and embedded in different games. This project will also contribute patterns and an understanding of how people learn and engage in problem solving using concepts of abstraction, modularity, debugging and semantics. These outcomes will lead to advancement in knowledge in the learning sciences as well as the design of educational games that enrich STEM learning, particularly in programming and computational thinking. In addition, this project will engage female participants and underserved populations through partnering organizations including National Girls Collaborative project.
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.
DATE:
-
TEAM MEMBERS:
Magy Seif El-Nasr
resourceprojectProfessional Development, Conferences, and Networks
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 a two-day conference, along with pre- and post-conference activities, with the goal of furthering the informal science learning field's review of the research and development that has been conducted on data visualizations that have been used to help the public better understand and become more engaged in science. The project will address an urgent need in informal science education, providing a critical first step towards a synthesis of research and technology development in visualization and, thus, to inform and accelerate work in the field in this significant and rapidly changing domain.
The project will start with a Delphi study by the project evaluator prior to the conference to provide an Emerging Field Assessment on data visualization work to date. Then, a two-day conference at the Exploratorium in San Francisco and related activities will bring together AISL-funded PIs, computer scientists, cognitive scientists, designers, and technology developers to (a) synthesize work to date, (b) bring in relevant research from fields outside of informal learning, and (c) identify remaining knowledge gaps for further research and development. The project team will also develop a website with videos of all presentations, conference documentation, resources, and links to social media communities; and a post-conference publication mapping the state of the field, key findings, and promising technologies.
The initiative also has a goal to broaden participation, as the attendees will include a diverse cadre of professionals in the field who contribute to data visualization work.
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.
This project, an NSF INCLUDES Design and Development Launch Pilot, managed by the University of Nevada, Reno, addresses the grand challenge of increasing underrepresentation regionally in the advanced manufacturing sector. Using the state's Learn and Earn Program Advanced Career Pathway (LEAP) as the foundation, science, technology, engineering and mathematics (STEM) activities will support and prepare Hispanic students for the region's workforce in advanced manufacturing which includes partnerships with Truckee Meadows Community College (TMCC), the state's Governor's Office of Economic Development, Charles River Laboratories, Nevada Established Program to Stimulate Competitive Research (Nevada EPSCoR) and the K-12 community.
The expected outcomes from the project will inform the feasibility, expandability and transferability of the LEAP framework in diversifying the state's workforce locally and the STEM workforce nationally. Formative and summative evaluation will be conducted with a well-matched comparison group. Dissemination of project results will be disseminated through the Association for Public Land-Grant Universities (APLU), STEM conferences and scholarly journals.
DATE:
-
TEAM MEMBERS:
David ShintaniJulie EllsworthKarsten HeiseRobert StachlewitzRegina Tempel
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.
DATE:
-
TEAM MEMBERS:
Ila BermanT. Donna ChenKaren RheubanQian Cai
Women continue to be underrepresented in computer science professions. In 2015, while 57% of professional occupations in the U.S. were held by women, only 25% of computing occupations were held by women. Furthermore, the share of computer science degrees going to women is smaller than any STEM field, even though technology careers are the most promising in terms of salaries and future growth. Research suggests that issues contributing to this lack of computer science participation begin early and involve complex social and environmental factors, including girls' perception that they do not belong in computer science classes or careers. Computer science instruction often alienates girls with irrelevant curriculum; non-collaborative pedagogies; a lack of opportunities to take risks or make mistakes; and a heavy reliance on lecture instead of hands-on, project-based learning. Computer science experiences that employ research-based gender equitable best practices, particularly role modeling, can help diminish the gender gap in participation. In response to this challenge, Twin Cities PBS (TPT), the National Girls Collaborative (NGC) and Code.org will lead Code: SciGirls! Media for Engaging Girls in Computing Pathways, a three-year project designed to engage 8-13 year-old girls in coding through transmedia programming which inspires and prepares them for future computer science studies and career paths. The project includes five new PBS SciGirls episodes featuring girls and female coding professionals using coding to solve real problems; a new interactive PBSKids.org game that allows children to develop coding skills; nationwide outreach programming, including professional development for informal educators and female coding professionals to facilitate activities for girls and families in diverse STEM learning environments; a research study that will advance understanding of how the transmedia components build girls' motivation to pursue additional coding experiences; and a third-party summative evaluation.
Code: SciGirls! will foster greater awareness of and engagement in computer science studies and career paths for girls. The PBS SciGirls episodes will feature girls and female computer science professionals using coding to solve real-world challenges. The project's transmedia component will leverage the television content into the online space in which much of 21st century learning takes place. The new interactive PBSKids.org game will use a narrative framework to help children develop coding skills. Drawing on narrative transportation theory and character identification theory, TPT will commission two exploratory knowledge-building studies to investigate: To what extent and how do the narrative formats of the Code: SciGirls! online media affect girls' interest, beliefs, and behavioral intent towards coding and code-related careers? The studies aim to advance understanding of how media builds girls' motivation to pursue computer science experiences, a skill set critical to building tomorrow's workforce. The project team will also raise educators' awareness about the importance of gender equitable computer science instruction, and empower them with best practices to welcome, prepare and retain girls in coding. The Code: SciGirls! Activity Guide will provide educators with a relevant resource for engaging aspiring computer scientists. The new media and guide will also reside on PBSLearningMedia.org, reaching 1.2 million teachers, and will be shared with thousands of educators across the SciGirls CONNECT and National Girls Collaborative networks. The new episodes are anticipated to reach 92% of U.S. TV households via PBS, and the game at PBSKids.org will introduce millions of children to coding. The summative evaluation will examine the reach and impact of the episodes, game and new activities. PIs will share research findings and project resources at national conferences and will submit to relevant publications. This 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. 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.
To reach its full potential in science, technology, engineering, and mathematics (STEM), the United States must continue to recruit, prepare and maintain a diverse STEM workforce. Much work has been done in this regard. Yet, underrepresentation in STEM fields persists and is especially pronounced for Hispanic STEM professionals. The Hispanic community is the youngest and fastest growing racial/ethnic group in the United States but comprises only seven percent of the STEM workforce. More evidence-based solutions and innovative approaches are required. This project endeavors to address the challenges of underrepresentation in STEM, especially among individuals of Hispanic descent, through an innovative approach. The University of San Diego will design, develop, implement, and test a multilayered STEM learning approach specific to STEM learning and workforce development in STEM fields targeting Hispanic youth. The STEM World of Work project will explore youth STEM identity through three mechanisms: (1) an assessment of their individual interests, strengths, and values, (2) exposure to an array of viable STEM careers, and (3) engagement in rigorous hands-on STEM activities. The project centers on a youth summer STEM enrichment program and a series of follow-up booster sessions delivered during the academic year in informal contexts to promote family engagement. Paramount to this work is the core focus on San Diego's Five Priority Workforce Sectors: Advanced Manufacturing, Information and Communications Technology, Clean Energy, Healthcare, and Biotech. Few, if any, existing projects in the Advancing Informal STEM learning portfolio have explored the potential connections between these five priority workforce sectors, informal STEM learning, and identity among predominately Hispanic youth and families engaged in a year-long, culturally responsive STEM learning and workforce focused program. If successful, the model could provide a template for the facilitation of similar efforts in the future.
The STEM World of Work project will use a mixed-methods, exploratory research design to better understand the variables influencing STEM learning and academic and career choices within the proposed context. The research questions will explore: (1) the impacts of the project on students' engagement, STEM identity, STEM motivation, and academic outcomes, (2) factors that moderate these outcomes, and (3) the impact the model has on influencing youths' personal goals and career choices. Data will be garnered through cross-sectional and longitudinal surveys and reflective focus groups with the students and their parents/guardians. Multivariate analysis of variance, longitudinal modeling, and qualitative analysis will be conducted to analyze and report the data. The findings will be disseminated using a variety of methods and platforms. The broader impacts of the findings and work are expected to extend well beyond the project team, graduate student mentors, project partners, and the estimated 120 middle school students and their families from the predominately Hispanic Chula Vista Community of San Diego who will be directly impacted by the project.
This exploratory pathways 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. 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.
DATE:
-
TEAM MEMBERS:
Perla MyersVitaliy PopovOdesma DalrympleYaoran LiJoi Spencer
Becoming computationally literate is increasingly crucial to everyday life and to expanding workforce capacity. Research suggests that computational literacy--knowing what, when, how, and why to use the ideas of computer science, in combination with the capacity to view problems and potential solutions through the lens of computational structures and procedures--can be supported through digital game play. This project aims to develop a social and creative exhibit game that foregrounds aspects of computer science, specifically artificial intelligence (AI) and computer programming, in ways that enable youth to explore, construct, and share computational complex systems content with one another and other museum visitors. To play the game, pairs of youth visitors will use code cards to program the behavior of AI animals in a virtual forest. As they do so, youth will engage with computational literacy practices, such as basic computer programming, describing their computational ideas, and doing computational problem solving with their friends. Their activity will be projected on a large screen as a strategy for enabling youth to test, rehearse, and communicate their computational ideas and to also interest other visitors into computational problem solving.
Using multi-perspective and iterative design-based research, university learning scientists, museum practitioners, and game developers will pursue research questions around how science museums can better engage youth who are traditionally underrepresented in computer science in complex computational practices. Data sources will include interactive-log data, observations of visitor interactions with the game, visitor interviews, and visitor surveys. A multimodal and mixed methods approach that searches for convergences between qualitative analysis, quantitative analysis, and learning analytics will be used to generate research findings. Changes in computational literacy will be assessed by evaluating what problems visitors choose to solve with programming, how they frame those problems, and their selections from among possible solutions, what they program, how they program, and how they describe programming ideas. The results of this project will include: 1) a social, interactive gameplay experience that supports the development of computational literacy; 2) design principles for game-based exhibits that facilitate development of computational literacy; and 3) new knowledge of variations in design and gameplay across diverse gameplay users, including those from underrepresented groups in computer science. It is anticipated that 1,000 museum youth visitors will directly participate in the study.
This 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. 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.
DATE:
-
TEAM MEMBERS:
Matthew BerlandLeilah LyonsMatthew Cannady
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.
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.