Data science is ever-present in modern life. The need to learn with and about data science is becoming increasingly important in a world where the quantity of data is constantly growing, where one’s own data are often being harvested and marketed, where data science career opportunities are rapidly increasing, and where understanding statistics, data sources, and data representation is integral to understanding STEM and the world around us. Museums have the opportunity to play a critical role in introducing the public to data science concepts in ways that center personal relevance, social connections and collaborative learning. However, data science and statistics are difficult concepts to distill and provide meaningful engagement with during the brief learning experiences typical to science museums. This Pilot and Feasibility study brings together data scientists, data science educators, and museum exhibit designers to consider these questions:
What are the important data science concepts for the public to explore and understand in museum exhibits?
How can museum exhibits be designed to support visitors with diverse backgrounds and experiences to engage with these data science concepts?
What principles can shape these designs to promote broadening participation in data science specifically and STEM more broadly?
This Pilot and Feasibility project combines multidisciplinary expert convening, feasibility testing, and early exploratory prototyping around the focal topic of data science exhibits. Project partners, TERC, the Museum of Science, Boston, and The Tech Interactive in San Jose will engage in an iterative process to develop a theoretical grounding and practical guidance for museum practitioners. The project will include two convenings, bringing together teams of experts from the fields of data science, data science education and museum exhibit design. Prior to the first convening, an initial literature summary and a survey of convening participants will be conducted, culminating in a preliminary list of big ideas about data science. Periodically, participants will have the opportunity to rank, annotate and expand this list, as a form of ongoing data collection. During the convenings, participants will explore the preliminary list, share related work from the three disciplines, engage with related data science activities in small groups, and work together to build consensus around promising data science topics and approaches for exhibits. Participant evaluation will allow for iterative improvement of the convenings and the capture of missed points or overlooked topics. After each convening, museum partners will create prototypes that respond to the convening conversations. Prototypes will be pilot tested (evaluated) with an intentionally recruited group of families that includes both frequent visitors and those who are less likely to visit the museum; diversity in terms of race, languages and dis/ability will be reflected in selection. Pilot data collection will consist of structured observations and interviews. Results from the first round of prototyping will be shared with convening participants as a way to modify the list of big ideas and to further interrogate the feasibility of communicating these ideas in an exhibit format. Results from the convenings and from both rounds of prototyping will be combined in a guiding document that will be shared on all three partner websites, and more broadly with the informal STEM learning field. The team will also host a workshop for practitioners interested in designing data science exhibits, and present at a conference focused on museum exhibits and their design.
This project is expanding an effective mobile making program to achieve sustainable, widespread impact among underserved youth. Making is a design-based, participant-driven endeavor that is based on a learning by doing pedagogy. For nearly a decade, California State University San Marcos has operated out-of-school making programs for bringing both equipment and university student facilitators to the sites in under-served communities. In collaboration with four other CSU campuses, this project will expand along four dimensions: (a) adding community sites in addition to school sites (b) adding rural contexts in addition to urban/suburban, (c) adding hybrid and online options in addition to in-person), and (d) including future teachers as facilitators in addition to STEM undergraduates. The program uses design thinking as a framework to engage participants in addressing real-world problems that are personally and socially meaningful. Participants will use low- and high-tech tools, such as circuity, coding, and robotics to engage in activities that respond to design challenges. A diverse group of university students will lead weekly, 90-minute activities and serve as near-peer mentors, providing a connection to the university for the youth participants, many of whom will be first-generation college students. The project will significantly expand the Mobile Making program from 12 sites in North San Diego County to 48 sites across California, with nearly 2,000 university facilitators providing 12 hours of programming each year to over 10,000 underserved youth (grades 4th through 8th) during the five-year timeline.
The project research will examine whether the additional sites and program variations result in positive youth and university student outcomes. For youth in grades 4 through 8, the project will evaluate impacts including sustained interest in making and STEM, increased self-efficacy in making and STEM, and a greater sense that making and STEM are relevant to their lives. For university student facilitators, the project will investigate impacts including broadened technical skills, increased leadership and 21st century skills, and increased lifelong interest in STEM outreach/informal science education. Multiple sources of data will be used to research the expanded Mobile Making program's impact on youth and undergraduate participants, compare implementation sites, and understand the program's efficacy when across different communities with diverse learner populations. A mixed methods approach that leverages extant data (attendance numbers, student artifacts), surveys, focus groups, making session feedback forms, observations, and field notes will together be used to assess youth and university student participant outcomes. The project will disaggregate data based on gender, race/ethnicity, grade level, and site to understand the Mobile Making program's impact on youth participants at multiple levels across contexts. The project will further compare findings from different types of implementation sites (e.g., school vs. library), learner groups, (e.g., middle vs. upper elementary students), and facilitator groups (e.g., STEM majors vs. future teachers). This will enable the project to conduct cross-case comparisons between CSU campuses. Project research will also compare findings from urban and rural school sites as well as based on the modality of teaching and learning (e.g., in-person vs. online). The mobile making program activities, project research, and a toolkit for implementing a Mobile maker program will be widely disseminated to researchers, educators, and out-of-school programs.
This poster was presented at the 2021 NSF AISL Awardee Meeting.
Since 2006, the National High Magnetic Field Laboratory (MagLab) through the Center for Integrating Research and Learning (CIRL) has offered a SciGirls Summer Camp to introduce middle school girls to various fields of science. Code: SciGirls was created in 2017 to increase the engagement in computer science studies and career paths for girls. This consistent commitment to girls in STEM led the SciGirls creators at Twin Cities Public Television (TPT) to invite CIRL to be a partner with them. In the summer of 2021, CIRL & TPT
Wireless radio communications, such as Wi-Fi, transmit public and private data from one device to another, including cell phones, computers, medical equipment, satellites, space rockets, and air traffic control. Despite their critical role and prevalence, many people are unfamiliar with radio waves, how they are generated and interact with their surroundings, and why they are the basis of modern communication and navigation. This topic is not only increasingly relevant to the technological lives of today’s youth and public, it is critical to the National Science Foundation’s Industries of the Future activities, particularly in advancing wireless education and workforce development. In this project, STEM professionals from academia, industry and informal education will join forces to design, evaluate, and launch digital apps, a craft-based toolkit, activity guides, and mobile online professional learning, all of which will be easily accessed and flexibly adapted by informal educators to engage youth and the public about radio frequency communications. Experiences will include embodied activities, such as physically linking arms to create and explore longitudinal and transverse waves; mobile experiences, such as augmented reality explorations of Wi-Fi signals or collaborative signal jamming simulations; and technological exploration, such as sending and receiving encrypted messages.
BSCS Science Learning, Georgia Tech, and the Children’s Creativity Museum (CCM) with National Informal STEM Education Network (NISE Net) museum partners will create pedagogical activity designs, digital apps, and a mobile online professional learning platform. The project features a rigorous and multipronged research and development approach that builds on prior learning sciences studies to advance a learning design framework for nimble, mobile informal education, while incorporating the best aspects of hands-on learning. This project is testing two related hypotheses: 1) a mobile strategy can be effective for supporting just-in-time informal education of a highly technical, scientific topic, and 2) a mobile suite of resources, including professional learning, can be used to teach informal educators, youth, and the general public about radio frequency communications. Data sources include pre- and post- surveys, interviews, and focus groups with a wide array of educators and learners.
A front-end study will identify gaps in public understanding and perceptions specific to radio frequency communications, and serve as a baseline for components of the summative research. Iterative formative evaluation will incorporate participatory co-design processes with youth and informal educators. These processes will support materials that are age-appropriate and culturally responsive to not only youth, with an emphasis on Latinx youth, but also informal educators and the broader public. Summative evaluation will examine the impact of the mobile suite of resources on informal educators’ learning, facilitation confidence and intentions to continue to incorporate the project resources into their practice. The preparation of educators in supporting public understanding of highly technological STEM topics can be an effective way for supporting just-in-time public engagement and interests in related careers. Data from youth and museum visitors will examine changes to interest, science self-efficacy, content knowledge, and STEM-related career interest. If successful, this design approach may influence how mobile resources are designed and organized effectively to impact future informal education on similarly important technology-rich topics. All materials will be released under Creative Commons licenses allowing for widespread sharing and remixing; research and design findings will be published in academic, industry, and practitioner journals.
This project is co-funded by two NSF programs: 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. The Innovative Technology Experiences for Students and Teachers (ITEST) program, which supports projects that build understandings of practices, program elements, contexts and processes contributing to increasing students' knowledge and interest in science, technology, engineering, and mathematics (STEM) and information and communication technology (ICT) careers.
This 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.
The Council for Opportunity in Education, in collaboration with TERC, seeks to advance the understanding of social and cultural factors that increase retention of women of color in computing; and implement and evaluate a mentoring and networking intervention for undergraduate women of color based on the project's research findings. Computing is unique because it ranks as one of the STEM fields that are least populated by women of color, and because while representation of women of color is increasing in nearly every other STEM field, it is currently decreasing in computing - even as national job prospects in technology fields increase. The project staff will conduct an extensive study of programs that have successfully served women of color in the computing fields and will conduct formal interviews with 15 professional women of color who have thrived in computing to learn about their educational strategies. Based on those findings, the project staff will develop and assess a small-scale intervention that will be modeled on the practices of mentoring and networking which have been established as effective among women of color who are students of STEM disciplines. By partnering with Broadening Participation in Computing Alliances and local and national organizations dedicated to diversifying computing, project staff will identify both women of color undergraduates to participate in the intervention and professionals who can serve as mentors to the undergraduates in the intervention phase of the project. Assisting the researchers will be a distinguished Advisory Board that provides expertise in broadening the representation of women of color in STEM education. The external evaluator will provide formative and summative assessments of the project's case study data and narratives data using methods of study analysis and narrative inquiry and will lead the formative and summative evaluation of the intervention using a mixed methods approach. The intervention evaluation will focus on three variables: 1) students' attitudes toward computer science, 2) their persistence in computer science and 3) their participant attitudes toward, and experiences in, the intervention.
This project extends the PIs' previous NSF-funded work on factors that impact the success of women of color in STEM. The project will contribute an improved understanding of the complex challenges that women of color encounter in computing. It will also illuminate individual and programmatic strategies that enable them to participate more fully and in greater numbers. The ultimate broader impact of the project should be a proven, scalable model for reversing the downward trend in the rates at which women of color earn bachelor's degrees in computer science.
The Council for Opportunity in Education, in collaboration with TERC, seeks to advance the understanding of social and cultural factors that increase retention of women of color in computing; and implement and evaluate a mentoring and networking intervention for undergraduate women of color based on the project's research findings. Computing is unique because it ranks as one of the STEM fields that are least populated by women of color, and because while representation of women of color is increasing in nearly every other STEM field, it is currently decreasing in computing - even as national job prospects in technology fields increase. The project staff will conduct an extensive study of programs that have successfully served women of color in the computing fields and will conduct formal interviews with 15 professional women of color who have thrived in computing to learn about their educational strategies. Based on those findings, the project staff will develop and assess a small-scale intervention that will be modeled on the practices of mentoring and networking which have been established as effective among women of color who are students of STEM disciplines. By partnering with Broadening Participation in Computing Alliances and local and national organizations dedicated to diversifying computing, project staff will identify both women of color undergraduates to participate in the intervention and professionals who can serve as mentors to the undergraduates in the intervention phase of the project. Assisting the researchers will be a distinguished Advisory Board that provides expertise in broadening the representation of women of color in STEM education. The external evaluator will provide formative and summative assessments of the project's case study data and narratives data using methods of study analysis and narrative inquiry and will lead the formative and summative evaluation of the intervention using a mixed methods approach. The intervention evaluation will focus on three variables: 1) students' attitudes toward computer science, 2) their persistence in computer science and 3) their participant attitudes toward, and experiences in, the intervention.
This project extends the PIs' previous NSF-funded work on factors that impact the success of women of color in STEM. The project will contribute an improved understanding of the complex challenges that women of color encounter in computing. It will also illuminate individual and programmatic strategies that enable them to participate more fully and in greater numbers. The ultimate broader impact of the project should be a proven, scalable model for reversing the downward trend in the rates at which women of color earn bachelor's degrees in computer science.
Counterspaces in science, technology, engineering, and mathematics (STEM) are often considered “safe spaces” at the margins for groups outside the mainstream of STEM education. The prevailing culture and structural manifestations in STEM have traditionally privileged norms of success that favor competitive, individualistic, and solitary practices—norms associated with White male scientists. This privilege extends to structures that govern learning and mark progress in STEM education that have marginalized groups that do not reflect the gender, race, or ethnicity conventionally associated with
Overlaying Computer Science (CS) courses on top of inequitable schooling systems will not move us toward “CS for All.” This paper prioritizes the perspectives of minoritized students enrolled in high school CS classrooms across a large, urban school district in the Western United States, to help inform how CS can truly be for all.
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TEAM MEMBERS:
Jean RyooTiera TanksleyCynthia EstradaJane Margolis
This award takes an innovative approach to an ongoing, pervasive, and persistent societal issue: women are still drastically underrepresented in computing careers. This project targets middle school-aged girls because it is a time when many of them lose interest and confidence in pursuing technical education and computing careers. This project will design, develop, and deploy a one-week experience focused on middle school girls that targets this issue with a novel combination of teaching techniques and technology. The project will use wearable computing devices to support girls' social interactions as they learn computing and solve technical challenges together. The goals of the project are to raise interest, perceived competence, and involvement in the computational ability of girls. Additionally, the project aims to increase a sense of computational community for girls that makes pursuing computational skills more relevant to their identities and lives, and that helps continued participation in computing. The project will deploy a one-week experience four times per year with a socioeconomically diverse range of campers. The project will also develop a 'program in a box' kit that can be broadly used by others wishing to deliver a similar experience for girls.
The planned research will determine if a one-week experience that uses social wearable construction in the context of live-action role play can use the mediating process of computational community formation to positively impact middle school girls' engagement with and interest in computation. Computational community is defined as girls engaging together in the process of learning computation, trading resources and knowledge, and supporting growth. Research participants will include 100 6th to 9th-grade girls. At least 75% of the participants will be either low income, first-generation college-bound, or underrepresented in higher education. Students will be recruited through the longstanding partnerships with title one schools in the Salinas Valley, the Educational Partnership Center, and in the Pajaro Valley Unified School district, where 82% of the students are Hispanic/Latinx, 42% are English Learners, and 73% are eligible for free or reduced lunch. The research questions are: 1) Does the proposed experience increase girls' self-reported competence, self-efficacy, and interest in computational skills and careers? and 2) Will the proposed experience lead to activity-based evidence of learning and integration of computational skills at the group social level? The project will use a mixed-methods, design-based research approach which is an iterative design process to rapidly collect and analyze data, and regularly discuss the implications for practice with the design team. Data will be collected using observations, interviews, focus groups, surveys, and staff logs. Quantitative data will be analyzed using frequencies, means, and measures of dispersion will be applied to survey data from both time points. Pearson correlation coefficients will be used to describe the bivariate relationship between continuous factors. ANOVAs will assess whether there are significant differences in continuous measures across groups. Qualitative data will be analyzed using a constant comparison method.
This Innovations in Development award is funded by the Advancing Informal STEM Learning (AISL) program, which seeks to advance new approaches to, and evidence-based understanding of, the design and development of STEM learning in informal environments. This includes providing multiple pathways for broadening access to and engagement in STEM learning experiences.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
We explored the potential of science to facilitate social inclusion with teenagers who had interrupted their studies before the terms set for compulsory education. The project was carried out from 2014 to 2018 within SISSA (International School for Advanced Studies), a scientific and higher education institution in physics, mathematics and neurosciences, and was focused on the production of video games using Scratch. The outcomes are encouraging: through active engagement, the participants have succeeded in completing complex projects, taking responsibilities and interacting with people
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TEAM MEMBERS:
Simona CerratoFrancesca RizzatoLucia TealdiElena Canel
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