This INSPIRE award is partially funded by the Cyber-Human Systems Program in the Division of Information and Intelligent Systems in the Directorate for Computer Science and Engineering, the Gravitational Physics Program in the Division of Physics in the Directorate for Mathematical and Physical Sciences, and the Office of Integrative Activities.
This innovative project will develop a citizen science system to support the Advanced Laser Interferometer Gravitational wave Observatory (aLIGO), the most complicated experiment ever undertaken in gravitational physics. Before the end of this decade it will open up the window of gravitational wave observations on the Universe. However, the high detector sensitivity needed for astrophysical discoveries makes aLIGO very susceptible to noncosmic artifacts and noise that must be identified and separated from cosmic signals. Teaching computers to identify and morphologically classify these artifacts in detector data is exceedingly difficult. Human eyesight is a proven tool for classification, but the aLIGO data streams from approximately 30,000 sensors and monitors easily overwhelm a single human. This research will address these problems by coupling human classification with a machine learning model that learns from the citizen scientists and also guides how information is provided to participants. A novel feature of this system will be its reliance on volunteers to discover new glitch classes, not just use existing ones. The project includes research on the human-centered computing aspects of this sociocomputational system, and thus can inspire future citizen science projects that do not merely exploit the labor of volunteers but engage them as partners in scientific discovery. Therefore, the project will have substantial educational benefits for the volunteers, who will gain a good understanding on how science works, and will be a part of the excitement of opening up a new window on the universe.
This is an innovative, interdisciplinary collaboration between the existing LIGO, at the time it is being technically enhanced, and Zooniverse, which has fielded a workable crowdsourcing model, currently involving over a million people on 30 projects. The work will help aLIGO to quickly identify noise and artifacts in the science data stream, separating out legitimate astrophysical events, and allowing those events to be distributed to other observatories for more detailed source identification and study. This project will also build and evaluate an interface between machine learning and human learning that will itself be an advance on current methods. It can be depicted as a loop: (1) By sifting through enormous amounts of aLIGO data, the citizen scientists will produce a robust "gold standard" glitch dataset that can be used to seed and train machine learning algorithms that will aid in the identification task. (2) The machine learning protocols that select and classify glitch events will be developed to maximize the potential of the citizen scientists by organizing and passing the data to them in more effective ways. The project will experiment with the task design and workflow organization (leveraging previous Zooniverse experience) to build a system that takes advantage of the distinctive strengths of the machines (ability to process large amounts of data systematically) and the humans (ability to identify patterns and spot discrepancies), and then using the model to enable high quality aLIGO detector characterization and gravitational wave searches
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TEAM MEMBERS:
Vassiliki KalogeraAggelos KatsaggelosKevin CrowstonLaura TrouilleJoshua SmithShane LarsonLaura Whyte
Reconceptualizing STEM + Computing Literacy is funded by the STEM+Computing Partnership (STEM+C) program, which seeks to advance multidisciplinary integration of computing and computational thinking in K-12 science, technology, engineering, and mathematics (STEM) teaching and learning through applied research and development across one or more domains, and broadening participation in computing and computing-related fields. The project will study the integration of computational thinking as part of a new and more contemporary perspective of STEM literacy, and will design, develop, and beta-test a prototype literacy assessment tool that will measure computational thinking literacy along with measures of literacy in other STEM content areas. The tool will be available to the general public as a self-measurement application (App) that can be used by individuals to test their own literacy, and by teachers, schools, and informal educators and organizations to assess literacy development in their students and in their STEM education programs. This transdisciplinary research project will begin the process of creating an innovative approach and tool for measuring literacy that will expand the definition of literacy to include computational skills along with science reasoning. Literacy is an important concept and measurement that has traditionally been used to assess an individual's knowledge of science. This project will explore a broader literacy perspective that incorporates learning derived from out of school and one that incorporates computational skills and thinking as part of a more contemporary perspective of STEM literacy. A prototype web-based App allowing individuals and education organizations to assess literacy levels, and ways to enhance literacy, will be developed and studied. The methodology will be developed using discussions and knowledge from over 60 experts across computing, education, science, social science, and other STEM fields using a Delphi method to engage in reconceptualization of literacy. The hypothesis is that this new STEM+C literacy framework should be structured along four interacting but semi-independent domains: 1) general STEM+C knowledge; 2) self-defined areas of STEM+C knowledge and expertise; 3) attitudes and beliefs related to STEM+C; and 4) the skills and competencies necessary to participate in STEM+C related pursuits and discussions, including measures of modes of STEM+C thinking. Each of these four domains is likely to include numerous sub-domains and associated descriptors, which collectively describe the different aspects of being a STEM+C literate citizen. The application will be designed to provide feedback to individuals on their knowledge, attitudes and skills compared with those of others and suggest ways to enhance and improve their skills and understanding through an embedded feedback mechanism. This project creates public benefit by providing individuals and organizations with a responsive real-time understanding measuring STEM+C literacy, deepening the dialogue about the value of public engagement in science, engineering, technology, math and computing and revealing the dynamic factors that inform STEM+C literacy.
The Cyberlearning and Future Learning Technologies Program funds efforts that will help envision the next generation of learning technologies and advance what we know about how people learn in technology-rich environments. Cyberlearning Exploration (EXP) Projects explore the viability of new kinds of learning technologies by designing and building new kinds of learning technologies and studying their possibilities for fostering learning and challenges to using them effectively. This project brings together two approaches to help K-12 students learn programming and computer science: open-ended learning environments, and computer-based learning analytics, to help create a setting where youth can get help and scaffolding tailored to what they know about programming without having to take tests or participate in rigid textbook exercises for the system to know what they know.
The project proposes to use techniques from educational data mining and learning analytics to process student data in the Alice programming environment. Building on the assessment design model of Evidence-Centered Design, student log data will be used to construct a model of individual students' computational thinking practices, aligned with emerging standards including NGSS and research on assessment of computational thinking. Initially, the system will be developed based on an existing corpus of pair-programming log data from approximately 600 students, triangulating with manually-coded performance assessments of programming through game design exercises. In the second phase of the work, curricula and professional development will be created to allow the system to be tested with underrepresented girls at Stanford's CS summer workshops and with students from diverse high schools implementing the Exploring Computer Science curriculum. Direct observation and interviews will be used to improve the model. Research will address how learners enact computational thinking practices in building computational artifacts, what patters of behavior serve as evidence of learning CT practices, and how to better design constructionist programming environments so that personalized learner scaffolding can be provided. By aligning with a popular programming environment (Alice) and a widely-used computer science curriculum (Exploring Computer Science), the project can have broad impact on computer science education; software developed will be released under a BSD-style license so others can build on it.
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TEAM MEMBERS:
Shuchi GroverMarie BienkowskiJohn Stamper
C-RISE will create a replicable, customizable model for supporting citizen engagement with scientific data and reasoning to increase community resiliency under conditions of sea level rise and storm surge. Working with NOAA partners, we will design, pilot, and deliver interactive digital learning experiences that use the best available NOAA data and tools to engage participants in the interdependence of humans and the environment, the cycles of observation and experiment that advance science knowledge, and predicted changes for sea level and storm frequency. These scientific concepts and principles will be brought to human scale through real-world planning challenges developed with our city and government partners in Portland and South Portland, Maine. Over the course of the project, thousands of citizens from nearby neighborhoods and middle school students from across Maine’s sixteen counties, will engage with scientific data and forecasts specific to Portland Harbor—Maine’s largest seaport and the second largest oil port on the east coast. Interactive learning experiences for both audiences will be delivered through GMRI’s Cohen Center for Interactive Learning—a state-of-the-art exhibit space—in the context of facilitated conversations designed to emphasize how scientific reasoning is an essential tool for addressing real and pressing community and environmental issues. The learning experiences will also be available through a public web portal, giving all area residents access to the data and forecasts. The C-RISE web portal will be available to other coastal communities with guidance for loading locally relevant NOAA data into the learning experience. An accompanying guide will support community leaders and educators to embed the interactive learning experiences effectively into community conversations around resiliency. This project is aligned with NOAA’s Education Strategic Plan 2015-2035 by forwarding environmental literacy and using emerging technologies.
Although major growth in engineering and computing jobs is expected in the next 10 years, students are not majoring in sufficient numbers to meet this demand. These impending workforce demands cannot be met without developing the skills of racial and ethnic minorities: however, Hispanics and Black/African Americans make up only a small percentage of doctoral students in the United States. The goal of the Consortium of Minority Doctoral Scholars (CMDS) Design and Development Launch Pilot is to broaden the participation of minorities in these fields. This pilot project will create a data portal that will allow the research team to study and understand the efficacy of various mentoring strategies that might be piloted across institutions and minority doctoral scholars programs.
Part II
The Consortium of Minority Doctoral Scholars (CMDS) will unite three of the nation's oldest and most prominent minority doctoral scholars programs (GEM, SREB and McKnight); organizations with a long history of impact in increasing the numbers of minorities obtaining advanced degrees. The CMDS Design and Development Launch Pilot will conduct extensive studies using data from these three programs. The research team will conduct a mixed method analysis of the data to discover commonalities and distinctions about the three programs' mentoring efforts as compared to students not involved in the three programs. This will result in a data-driven strategy for researching the efficacy of mentoring programs that can be applied across the three CMSD member and other minority doctoral scholars programs. By utilizing data from successful programs to pinpoint effective mentoring strategies, the project will create opportunities for larger numbers of minorities to be successful. This approach has implications not only with respect to equity and access, but also the development of a workforce that will drive future advances.
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TEAM MEMBERS:
Juan GilbertShaundra DailyJerlando Jackson
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.
As a part of its overall strategy to enhance learning in informal environments, the Advancing Informal STEM Learning (AISL) program funds research and innovative resources for use in a variety of settings. This media and technology project will scale up Youth Radio's proven model of STEM education through youth-driven multimedia journalism and related app development using the MIT App Inventor. A new Youth News Network (YNN) will implement a nationwide feeder system of youth reporters and educators using the previously developed and proven STEM curriculum. Previous research and evaluation has demonstrated that this model can engage underserved youth and put them in leadership positions in technological innovation. Key deliverables include the YNN STEM Desk that will produce 15-20 STEM-related stories each year; bootcamps (1-3 day workshops) training youth around the country focusing on app development and media links; and new toolkits providing resources to help with app development, data analysis and other STEM-specific skills. Project partners include MIT Media Lab, National Public Radio, Best Buy's Teen Tech Centers, National Writing Project, Computer Clubhouses, and PBS Learning Media among others.
Over the previous eight years, research and evaluation findings had been used to refine the project. These data served as the foundation for this scale-up project. The research conducted by the investigator and the Scholar-in-Residence in this scale-up uses an embedded ethnographic approach that combines field notes, recorded meetings and discussions, media artifacts, etc.--data that is transcribed and coded for indicators of STEM learning and critical computational literacy. The external summative evaluation will build on prior evidence regarding how this unique model engages youth and impacts their skills in STEM related media and technology.
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TEAM MEMBERS:
Elisabeth SoepEllin O'LearyHarold Abelson
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
This project will capitalize on the power of story to teach foundational computational thinking (CT) concepts through the creation of animated and live-action videos, paired with joint media engagement activities, for preschool children and their parents. Exposure at a young age to CT is critical for preparing all students to engage with the technologies that have become central to nearly every occupation. But despite this recognized need, there are few, if any, resources that (1) introduce CT to young children; (2) define the scope of what should be taught; and (3) provide evidence-based research on effective strategies for bringing CT to a preschool audience. To meet these needs, WGBH and Education Development Center/Center for Children and Technology (EDC/CCT) will utilize an iterative research and design process to create animated and live-action videos paired with joint media engagement activities for parents and preschool children, titled "Monkeying Around". Animated videos will model for children how to direct their curiosity into a focused exploration of the problem-solving process. Live-action videos will feature real kids and their parents and will further illustrate how helpful CT can be for problem solving. With their distinctive visual humor and captivating storytelling, the videos will be designed to entice parents to watch alongside their children. This is important since parents will play an important role in guiding them in explorations that support their CT learning. To further promote joint media engagement, hands-on activities will accompany the videos. Following the creation of these resources, an experimental impact study will be conducted to capture evidence as to if and how these resources encourage the development of young children's computational thinking, and to assess parents' comfort and interest in the subject. Concurrent with this design-based research process, the project will build on the infrastructure of state systems of early education and care (which have been awarded Race to the Top grants) and local public television stations to design and develop an outreach initiative to reach parents. Additional partners--National Center for Women & Information Technology, Code in Schools, and code.org (all of whom are all dedicated to promoting CT)--will further help bring this work to a national audience.
Can parent/child engagement with digital media and hands-on activities improve children's early learning of computational thinking? To answer this question, WGBH and EDC/CCT are collaborating on a design-based research process with children and their parents to create Monkeying Around successive interactions. The overarching goal of this mixed-methods research effort is to generate evidence that supports the development of recommendations around the curricular, instructional, and contextual factors that support or impede children's acquisition of CT as a result of digital media viewing and hands-on engagement. Moving through cycles of implementation, observation, analysis, and revision over the course of three years, EDC/CCT researchers will work closely with families and WGBH's development team to determine how children learn the fundamentals of CT, how certain learning tasks can demonstrate what children understand, how to stimulate interest in hands-on activities, and the necessary scaffolds to support parental involvement in the development of children's CT. Each phase of the research will provide rich feedback to inform the next cycle of content development and will include: Phase 1: the formulation of three learning blueprints (for algorithmic thinking, sequencing, and patterns); Phase 2: the development of a cohesive set of learning tasks to provide evidence of student learning, as well as the production of a prototype of the digital media and parent/child engagement resources (algorithmic thinking); Phase 3-Part A: pilot research on the prototype, revisions, production of two additional prototypes (sequencing and patterns); Phase 3-Part B: pilot research on the three prototypes and revisions; and Phase 4: production of 27 animated and live-action videos and 18 parent/child engagement activities and a study of their impact. Through this process, the project team will build broader knowledge about how to design developmentally appropriate resources promoting CT for preschool children and will generate data on how to stimulate interest in hands-on activities and the necessary scaffolds to support parental involvement in the development of children's CT. The entire project represents an enormous opportunity for WGBH and for the informal STEM media field to learn more about how media can facilitate informal CT learning in the preschool years and ways to broaden participation by building parents' capacity to support STEM learning. 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.
This project, a collaboration of teams at Georgia Institute of Technology, Northwestern University, and the Museum of Design Atlanta and the Museum of Science and Industry in Chicago, will investigate how to foster engagement and broadening participation in computing by audiences in museums and other informal learning environments that can transfer to at-home and in-school engagement (and vice versa). The project seeks to address the national need to make major strides in developing computing literacy as a core 21st century STEM skill. The project will adapt and expand to new venues their current work on their EarSketch system which connects computer programming concepts to music remixing, i.e. the manipulation of musical samples, beats and effects. The initiative involves a four-year process of iteratively designing and developing a tangible programming environment based on the EarSketch learning environment. The team will develop three new applications: TuneTable, a multi-user tabletop exhibit for museums; TunePad, a smaller version for use at home and in schools; and an online connection between the earlier EarSketch program and the two new devices.
The goal is to: a) engage museum learners in collaborative, playful programming experiences that create music; b) direct museum learners to further learning and computational music experiences online with the EarSketch learning environment; c) attract EarSketch learners from local area schools to visit the museum and interact with novice TuneTable users, either as mentors in museum workshops or museum guests; and d) inform the development of a smaller scale, affordable tangible-based experience that could be used at homes or in smaller educational settings, such as classrooms and community centers. In addition to the development of new learning experiences, the project will test the hypothesis that creative, playful, and social engagement in the arts with computer programming across multiple settings (e.g. museums, homes, and classrooms) can encourage: a) deeper learner involvement in computer programming, b) social connections to other learners, c) positive attitudes towards computing, and d) the use and recognition of computational concepts for personal expression in music. The project's knowledge-building efforts include research on four major questions related to the goals and evaluation processes conducted by SageFox on the fidelity of implementation, impact, success of the exhibits, and success of bridging contexts. Methods will draw on the Active Prolonged Engagement approach (unobtrusive observation, interviews, tracking-and-timing, data summaries and team debriefs) as well as Participatory Action Research methods.
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:
Michael HornBrian MagerkoJason Freeman
This project formed a partnership between a research team with experience in computer science (CS) education and learning sciences research and a newly fashioned practitioner team focused on building a grassroots, informal, volunteer group created to help women help themselves and others learn to write computer code. This research-practitioner partnership had a two-pronged focus, first on improving the program offered to learners through making adjustments based on research findings, and second on investigating the phenomenon of how women in the workforce informally learn CS skills that enable them to rewrite their career paths to contribute to what we know from research. The context of the study was situated in the virtual community that has formed around the phenomenally successful Salesforce Customer Relationship Management software platform.
This Exploratory Pathways project aimed to fill a gap in the research; we know little about the phenomenon of adult women in the workforce who are patching together resources to learn CS skills with a goal of job enhancement or job change. This project took an ethnographic approach to studying the informal learning (both through online, written resources and through sharing of knowledge with others) of the women involved in a 10-week, virtual Women’s Coaching and Learning group. The organization of this group consisted of learners—novice coders in the Apex language that is used on the Salesforce software platform, of coaches—more knowledgeable coders, and of a steering committee that ran the group and created the informal curriculum followed in the 10-week course.
Our overarching research question in this study was: In what ways are informal CS learning opportunities being used and created by adult women, what are their experiences with those opportunities, and how does this suggest ways to enhance those opportunities in the future to increase effectiveness in broadening access to and engagement in informal CS learning experiences for women?
We broke the question down into a number of sub questions, including:
Sociocultural context: What past gendered interactions do women report that discouraged (or encouraged) them from learning to code? What do interactions look like in female-only coaching and learning groups? In what ways does a coaching and learning group support persistence? What social barriers and supports outside the group affect persistence?
Personal context: What are the characteristics and backgrounds of female administrators who seek out resources to teach themselves to code? What are the motivations for these women to teach themselves to code? What motivates them to seek out and join all-women coding groups?
Physical context: How are women learning to code both through written resources and in virtual, informal coaching and learning classes? What are the conceptual barriers and supports that they encounter, and what works for women in these classes to overcome barriers? What conceptual barriers and supports affect persistence?
Persistence and identity: In what ways does participating in a learning group with female coaching motivate (or not) women to persist in learning to code? How do their goals or reasons for learning to code change through their participation? How does their identity as a “coder” change or shift as they participate?
Our findings for these subquestions are summarized in the “project products” linked to below.