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.
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TEAM MEMBERS:
Apriel HodariMaria Ong
resourceprojectProfessional Development, Conferences, and Networks
The Center for Integrated Quantum Materials pursues research and education in quantum science and technology. With our research and industry partners, the Museum of Science, Boston collaborates to produce public engagement resources, museum programs, special events and media. We also provide professional development in professional science communication for the Center's students, post-docs, and interns; and coaching in public engagement. The Museum also sponsors The Quantum Matters(TM) Science Communication Competition (www.mos.org/quantum-matters-competition) and NanoDays with a Quantum Leap. In association with CIQM and IBM Q, the Museum hosted the first U.S. museum exhibit on quantum computing.
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TEAM MEMBERS:
Robert WesterveltCarol Lynn AlpertRay AshooriTina Brower-Thomas
Computational Thinking (CT) is a relatively new educational focus and a clear need for learners as a 21st century skill. This proposal tackles this challenging new area for young learners, an area greatly in need of research and learning materials. The Principal Investigators will develop and implement integrated STEM+C museum exhibits and integrate CT in their existing engineering design based PictureSTEM curriculum for K-2 students. They will also pilot assessments of the CT components of the PictureSTEM curriculum. This work will make a unique contribution to the available STEM+C learning materials and assessments. There are few such materials for the kindergarten to second grade (K-2) population they will work with. They will research the effects of the curriculum and the exhibits with a mixed methods approach. First, they will collect observational data and conduct case studies to discover the important elements of an integrated STEM+C experience in both the formal in-school setting with the curriculum and in the informal out-of-school setting with families interacting with the museum exhibits. This work will provide a novel way to understand the important question of how in- and out-of-school experiences contribute to the development of STEM and CT thinking and learning. Finally, they will collect data from all participants to discover the ways that their activities lead to increases in STEM+C knowledge and interest.
The Principal Investigators will build on an integrated STEM curriculum by integrating CT and develop integrated museum exhibits. They base both activities on engineering design implemented through challenge based programming activities. They will research and/or develop assessments of both STEM+C integrated thinking and CT. Their research strategy combines Design Based Research and quantitative assessment of the effectiveness of the materials for learning CT. In the first two years of their study, they will engage in iterations on the design of the curriculum and the exhibits based on observation and case-study data. There will be 16 cases that draw from each grade level and involve data collection for the case student in both schools and museums. They will also use this work to illuminate what integrated STEM+C thinking and learning looks like across formal and informal learning environments. Based in some part on what they discover in this first phase, they will conduct the quantitative assessments with all (or at least most) students participating in the study
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
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.
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.
This project takes an ethnographic and design-based approach to understanding how and what people learn from participation in makerspaces and explores the features of those environments that can be leveraged to better promote learning. Makerspaces are physical locations where people (often families) get together to make things. Some participants learn substantial amounts of STEM content and practices as they design, build, and iteratively refine working devices. Others, however, simply take a trial and error approach. Research explores the affordances are of these spaces for promoting learning and how to integrate technology into these spaces so that they are transformed from being makerspaces where learning happens, but inconsistently, into environments where learning is a consistent outcome of participation. One aim is to learn how to effectively design such spaces so that participants are encouraged and helped to become intentional, reflective makers rather than simply tinkerers. Research will also advance what is known about effective studio teaching and learning and advance understanding of how to support youth to help them become competent, creative, and reflective producers with technology(s). The project builds on the Studio Thinking Framework and what is known about development of meta-representational competence. The foundations of these frameworks are in Lave and Wengers communities of practice and Rogoff's, Stevens et al.'s, and Jenkins et al.'s further work on participatory cultures for social networks that revolve around production. A sociocultural approach is taken that seeks to understand the relationships between space, participants, and technologies as participants set and work toward achieving goals. Engaging more of our young population in scientific and technological thinking and learning and broadening participation in the STEM workplace are national imperatives. One way to address these imperatives is to engage the passions of young people, helping them recognize the roles STEM content and practices play in achieving their own personal goals. Maker spaces are neighborhood spaces that are arising in many urban areas that allow and promote tinkering, designing, and construction using real materials, sometimes quite sophisticated ones. Participating in designing and successfully building working devices in such spaces can promote STEM learning, confidence and competence in one's ability to solve problems, and positive attitudes towards engineering, science, and math (among other things). The goal in this project is to learn how to design these spaces and integrate learning technologies so that learning happens more consistently (along with tinkering and making) and especially so that they are accessible and inviting to those who might not normally participate in these spaces. The work of this project is happening in an urban setting and with at-risk children, and a special effort is being made to accommodate making and learning with peers. As with Computer Clubhouses, maker spaces hold potential for their participants to identify what is interesting to them at the same time their participation gives them the opportunity to express themselves, learn STEM content, and put it to use.
This project is making novel use of familiar technology (smartphones and tablets) to address the immediate and pressing challenge of affordable, ongoing, large-scale museum evaluation, while encouraging museum visitors to engage deeply with museum content. Using a smartphone app, museum visitors pose questions to a 'virtual scientist' called Dr. Discovery (Dr. D). Dr. D provides answers and the chance to complete fun mini-challenges. The questions visitors ask are gathered in a large database. An analytics system analyzes these data and a password-protected website provides continuous, accessible evaluation data to museum staff, helping them make just-in-time tweaks (or longer term changes) to exhibit-related content (such as multimedia, lecture topics, docent training, experience carts, etc.) as current events and visitors' needs and interests change. The intellectual merit of this project is that it is building evaluation capacity among informal educators, advancing the fields of visitor studies, museum evaluation, informal science learning, and situated engagement, and is contributing to the development of novel evaluation techniques in museums. This project has many broader impacts: The Ask Dr. Discovery system is available to any venue that wishes to use or adapt it to their context. By enhancing the visitor experience and improving museum access to data for evaluation and data-driven decision making across the country, Ask Dr. Discovery has both a direct and indirect impact on museums and visitors of all types. This project is also training the next generation of STEM and education innovators by employing a diverse team of undergraduate students.
The Cyberlearning Resource Center (CRC) has responsibility for promoting integrative collaboration among cyberlearning grantees (across NSF programs); synthesis and national dissemination of cyberlearning findings, technologies, models, materials, and best practices; creating a national presence for Cyberlearning; helping the disparate Cyberlearning research and development communities coordinate efforts to build capacity; and providing infrastructure (technological and social) for supporting these efforts. Monitored through the Cyberlearning: Transforming Education program, the CRC serves as a resource for all NSF grantees and programs with cyberlearning components, helping to promote synergy and integrate projects across NSF's cyberlearning investments. Among society's central challenges are amplifying, expanding, and transforming opportunities people have for learning and more effectively drawing in, motivating, and engaging young learners. Engaging actively as a citizen and productively in the workforce requires understanding a broad variety of concepts and possessing the ability to collaborate, learn, solve problems, and make decisions. Whether learning is facilitated in school or out of school, and whether learners are youngsters or adults, to develop such knowledge and capabilities, learners must be motivated to learn, actively engage over the long term in learning activities, and put forth sustained cognitive and social effort. Consistent with NSF's mission and strategic plan, a variety of programs at NSF invest in research aimed towards achieving these goals. In support of this important thematic thrust, the Cyberlearning Resource Center works with researchers and NSF program officers to identify and disseminate findings from across programs and projects; develop ways to broker productive partnerships and collaborations; convene meetings for purposes of envisioning the future, integrating findings, and building capacity,; and monitor the cyberlearning portfolio and its influences and impacts.
EvalFest (Evaluation Use, Value, and Learning through Festivals of Science and Technology) will test innovative evaluation methods in science festivals that are being held across the country and assess in what ways and how effectively they are used. Morehead Planetarium and Science Center (at the University of North Carolina-Chapel Hill) and the University of California, San Francisco, in collaboration with over twenty science festivals, will (1) investigate whether a multisite evaluation approach is an effective model for creating common metrics for informal STEM education, (2) develop common methods to measure the effects of Festivals, (3) create a query-able database of 50,000 Festival attendees to share with the informal STEM learning field, and (4) document whether these efforts also result in new knowledge related to informal STEM education. The project will develop the Enterprise Feedback Management (EFM) system and query-able database for the festival community. EFMs are systems, including processes and software, that enable groups (such as the festival network) to collect, organize, analyze and share data. The EFM system will be designed to integrate data across sites and to allow users to extract data of interest. The project will refine evaluation tools currently used within the Science Festival Alliance that assess self-reported festival learning, and the effects of festival attendance, motivation, and future science participation. It will collect economic impact data and longitudinal festival attendee data. The project will also develop some new evaluation tools such as secret shopper observational protocols. Data from festival attendees will be collected onsite at participating festivals.
This early-stage design and development, integrated media and research project will contribute important new understandings to the informal science learning literature by exploring science engagement on social media when integrated with broadcast television. It will help answer questions including: What does such engagement look like? Who participates? How and why does it happen? and What is the degree or depth of engagement? The project builds on the previous successful work by WGBH nationally distributing the television series NOVA scienceNOW and the research expertise of EDC. WGBH's NOVA scienceNOW program will collaborate with EDC to develop new metrics to understand how and why learners engage with science on social media. Deliverables will include six one-hour episodes of NOVA scienceNOW, short online videos, moderated online discussion events, and an online film festival. A new social Media Initiative will develop six live broadcast microblogging events, six post-broadcast online discussion events, daily social media updates, and an online film festival that will feature user generated videos. A range of STEM content in the videos and online posts will be framed around big science and engineering questions such as animal communication and survival systems, the biology of sleep, climate change, new technologies, energy, genetics, and natural disasters. The continued innovations and expansion of social media channels provides significant new opportunities for providing learner's access to high quality science content, researchers, and opportunities to participate in science. In the first phase of this work to deepen the evidence based understanding of how social media supports informal science engagement, NOVA and EDC will collaborate to develop new measurement instruments: (1) a Network Profile to quantitatively represent the size and activity of NOVA's social media network; (2) an Informal Science Engagement (ISE) index to measure the degree of engagement by coding and analyzing conversations and posts; (3) a Follower Profile to assess the degree of activity and the nature of the engagement; and (4) a Science Social Media Engagement survey instrument. They will then use these measures and data collection protocols to explore whether and how the initiative might influence science engagement. External expert reviewers with content and methodological expertise will review all aspects of the project at critical junctures. This project will contribute important new knowledge and research instruments and methods to better understand how the learning opportunities of social media channels can be realized most effectively. This has significant potential for broad and lasting benefits to society as well as advancing the informal science learning field.