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
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
resourceresearchProfessional Development, Conferences, and Networks
A group of 12 researchers gathered at MSI to discuss issues surrounding the critical but challenging area of how to measure the long-term effects or impacts of ISE experiences, chaired by Dr. John Falk, Oregon State University and Institute for Learning Innovation, and hosted by Aaron Price, Museum of Science & Industry, Chicago, (MSI) on July 18, 2018. All the invitees had expertise and experience in this area, resulting in a rich conversation based equally in theory and practice. The goal of the discussion was to build on the collective experience of the group to identify and address key
This pilot study will examine the effectiveness of an innovative applied social change, community and technology based program on marginalized youths' access, interest, efficacy and motivation to learn and engage in digital technology applications. Using stratified near-peer and peer-to-peer mentoring approaches, the pilot builds on extant literature that indicates that peer-supported hands-on mentoring and experiences can alleviate some barriers to youth engagement in digital technologies, particularly among underrepresented groups. In this project, undergraduate students will mentor and work collaboratively with high school youth primarily of Hispanic descent and community-based organizations to develop creative technology-based solutions to address social issues and challenges within their local communities, culminating in events called Impactathons. These community-hosted local and state-wide events set this pilot project apart from similar work in the field. The Impactathons not only provide a space for intellectual discourse and problem-solving among the undergraduate-youth-community partners but the Impactathons will also codify expertise from scientists, social scientists, technologists, community leaders, and other stakeholders to develop technology-based solutions with real world application. If successful, a distal outcome will be increased youth interest in digital technologies and related fields. In the short term, favorable findings will provide preliminary evidence of success and lay the foundation for a more extensive study in the future.
This pilot project is a collaboration between the Everett Program, a student-led program for Technology and Social Change at the University of California Santa Cruz - a Hispanic Serving Institution - and the Digital NEST, a non-profit, high-tech youth career development and collaboration space for young people ages 14-24. Through this partnership and other recruitment efforts, an estimated 70-90 individuals will participate in the Impactathon pilot program over two years. Nearly two-thirds of the participants are expected to be undergraduate students. They will receive extensive training in near-peer and peer-to-peer mentoring and serve as mentors for and co-innovation developers with the high school youth participants. The undergraduates and youth will partner with local community organizations to identify a local social challenge that can be addressed through a technology-based solution. The emergent challenges will vary and could span the spectrum of STEM and applied social science topics of interest. Working in informal contexts (i.e., afterschool. weekend), the undergraduate-youth-community partner teams will work collaboratively to develop practical technology-based solutions to real world challenges. The teams will convene three times per year, locally and statewide, at student and community led Impactathons to share their work and glean insights from other teams to refine their innovations. In parallel, the research team will examine the effectiveness of the Impactathon model in increasing the undergraduate and youths' interest, motivation, excitement, engagement and learning of digital technologies. In addition to the research, the formative and summative evaluations should provide valuable insights on the effectiveness of the model and its potential for expansion and replication.
The project is co-funded by the Advancing Informal STEM Learning (AISL) Program and STEM +C. The AISL program seeks to advance new approaches to, and evidence-based understanding of, the design and development of STEM learning in informal environments. STEM + C focuses on research and development of interdisciplinary and transdisciplinary approaches to the integration of computing within STEM teaching and learning for preK-12 students in both formal and informal settings.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
This project tackles the urgent needs of the nation to engage people of all ages in computational thinking and help them learn basic computer science concepts with a unique and innovative approach of structured in-game computer program coding. Researchers will explore the design and development of a 3D puzzle-based game, called May's Journey, in which players solve an environmental maze by using the game's pseudo code to manipulate game objects. The game is designed to teach introductory but foundational concepts of computer programming including abstraction, modularity, reusability, and debugging by focusing players on logic and concepts while asking them to type simple instructions in a simplified programming language designed for novices. The game design in this project differs from today's block-based programming learning approaches that are often too far from actual computer code, and also differs from professional programming languages which are too complex for novices. The game and its embedded programming language learning are designed to be responsive to the progress of the learner throughout the game, transitioning from pseudo code to the embedded programming language itself. Error messages for debugging are also designed to be adaptive to players' behavior in the game. Using extensive log data collected from people playing the game, researchers can study how people learn computer programming. Such knowledge can advance understanding of the learning processes in computer programming education. Additionally, this work emphasizes the use of games as informal learning environments as they are accessible and fun, drawing attention and retention of many learners of different age groups with the potential to change attitudes towards computer programming across different populations. This project is co-funded by the STEM + Computing (STEM+C) program that supports research and development to understand the integration of computing and computational thinking in STEM learning, and the Advancing Informal STEM Learning (AISL) program that funds innovative research, approaches and resources for use in a variety of settings with its overall strategy to enhance learning in informal environments.
The project's formative and summative evaluation methods, including surveys, expert reviews of learners' computer code developed in the game, and interviews, are used to gauge learners' engagement as well as learning. In exploring learning, researchers aim to understand how players build implicit computer science knowledge through gameplay and how that gameplay relates to their performance on external transfer tasks. The project will answer the following three research questions: (1) Can observers reliably detect and label patterns of gameplay that provide evidence of learning or misconceptions regarding the four computer science constructs - abstraction, modularity, debugging and semantics - that learners exhibit playing May's Journey? (2) How does learner's implicit knowledge of these computer science constructs change over time and do those patterns vary by gender and prior programming experiences? (3) Is there a strong correlation between implicit learning measures and transfer of CS concepts: modularity, debugging, semantics, and abstraction? How do these correlations vary across elements of the game? This work will result in several outcomes: game design metaphors tested for their learning and engagement value that can be abstracted and embedded in different games. This project will also contribute patterns and an understanding of how people learn and engage in problem solving using concepts of abstraction, modularity, debugging and semantics. These outcomes will lead to advancement in knowledge in the learning sciences as well as the design of educational games that enrich STEM learning, particularly in programming and computational thinking. In addition, this project will engage female participants and underserved populations through partnering organizations including National Girls Collaborative project.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
The Science Behind Pixar (SBP) exhibition was the product of a collaborative effort among the Museum of Science, Boston (MOS), Pixar Animation Studios, and the Science Museum Exhibit Collaborative (SMEC). The 13,000 square foot exhibition presented the science, math, and computer science behind Pixar Animation Studios’ animated films and innovation. Before entering SBP, visitors watched a five-minute film that oriented them to the exhibition and discussed its main messages. Visitors then interacted with screen-based and physical interactive exhibits, as well as the technical pipeline of the
Cities and communities in the U.S. and around the world are entering a new era of transformational change, in which their inhabitants and the surrounding built and natural environments are increasingly connected by smart technologies, leading to new opportunities for innovation, improved services, and enhanced quality of life. The Smart and Connected Communities (SCC) program supports strongly interdisciplinary, integrative research and research capacity-building activities that will improve understanding of smart and connected communities and lead to discoveries that enable sustainable change to enhance community functioning. This project is a Research Coordination Network (RCN) that focuses on achieving SCC for medium/small size, remote, and rural communities through a polycentric (multiple centers) integrated policy, design, and technology approach. The communities served by the RCN have higher barriers to information, resources, and services than larger urban communities. To reduce this gap, the PIs propose to develop need-based R&D pipelines to select solutions with the highest potential impacts to the communities. Instead of trying to connect under-connected communities to nearby large cities, this proposal aims to develop economic opportunities within the communities themselves. This topic aligns well with the vision of the SCC program, and the proposed RCN consists of a diverse group of researchers, communities, industry, government, and non-profit partners.
This award will support the development of an RCN within the Commonwealth of Virginia which will coordinate multiple partners in developing innovations utilizing smart and connected technologies. The goal of the research coordination network is to enable researchers and citizens to collaborate on research supporting enhanced quality of life for medium, small, and rural communities which frequently lack the communication and other infrastructure available in cities. The research coordination network will be led by the University of Virginia. There are 14 partner organizations including six research center partners in transportation, environment, architecture and urban planning, and engineering and technology; two State and Industry partners (Virginia Municipal League and Virginia Center for Innovative Technology); four community partners representing health services (UVA Center for Telemedicine), small and remote communities (Weldon Cooper Center), neighborhood communities (Charlottesville Neighborhood Development), and urban communities (Thriving Cities); and two national partners which support high speed networking (US-Ignite) and city-university hubs (MetroLab). Examples of research coordination include telemedicine services, transportation services, and user-centric and community-centric utilization and deployment of sensor technologies.
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TEAM MEMBERS:
Ila BermanT. Donna ChenKaren RheubanQian Cai
Increasingly, the prosperity, innovation and security of individuals and communities depend on a big data literate society. Yet conspicuously absent from the big data revolution is the field of teaching and learning. The revolution in big data must match a complementary revolution in a new kind of literacy, through a significant infusion of STEM education with the kinds of skills that the revolution in 21st century data-driven science demands. This project represents a concerted effort to determine what it means to be a big data literate citizen, information worker, researcher, or policymaker; to identify the quality of learning resources and programs to improve big data literacy; and to chart a path forward that will bridge big data practice with big data learning, education and career readiness.
Through a process of inquiry research and capacity-building, New York Hall of Science will bring together experts from member institutions of the Northeast Big Data Innovation Hub to galvanize big data communities of practice around education, identify and articulate the nature and quality of extant big data education resources and draft a set of big data literacy principles. The results of this planning process will be a planning document for a Big Data Literacy Spoke that will form an initiative to develop frameworks, strategies and scope and sequence to advance lifelong big data literacy for grades P-20 and across learning settings; and devise, implement, and evaluate programs, curricula and interventions to improve big data literacy for all. The planning document will articulate the findings of the inquiry research and evaluation to provide a practical tool to inform and cultivate other initiatives in data literacy both within the Northeast Big Data Innovation Hub and beyond.
This INSPIRE project addresses the issue of high volume hydraulic fracturing, also called fracking, and its effects on ground water resources. Fracking allows drillers to extract natural gas from shale deep within the earth. Methane gas sometimes escapes from shale gas wells and can contaminate water resources or leak into the atmosphere where it contributes to greenhouse gas emissions. Monitoring for these potential leaks is difficult because methane is also released into aquifers naturally, and because monitoring is time- and resource-intensive. Such subsurface leakage may also be relatively rare. This project seeks to improve overall understanding of the impacts of natural gas drilling using both advances in computer science and geoscience, and to teach the public about such impacts. The project will elucidate both the effects of human activities such as shale gas development as well as natural processes which release methane into natural waters. Results of the proposed research will lead to a better understanding of water quality in areas of shale-gas development and will highlight problems and potentially problematic management practices. The research will advance both the fields of geoscience and computer science, will train interdisciplinary graduate students, and involve citizen scientists in collecting data and understanding environmental data analysis.
The project combines new hydro-geochemical strategies and data mining approaches to study the release of methane into streams and ground waters. For example, researchers will explore how to analyze the heterogeneous spatial data that describe distributions of methane concentrations in natural waters. The objectives of this project are to i) transform the ability to measure methane in streams; ii) train citizen scientists to work with project scientists to sample streams in an area of shale-gas development and publish large-volume datasets of methane in natural waters and aquifers; iii) innovate data mining and machine learning methods for environmental data to identify anomalous spots with potential leakage; iv) run field campaigns to measure methane concentrations and isotopic signatures of water samples in these spots; v) foster dialogue among nonscientists, consultants, university scientists, members of the gas industry, government agencies, and nonprofit organizations in and beyond the target region. Toward this end, the team will host workshops aimed to build dialogue among stakeholders and will release data analytic software for environmental measurements to benefit a broader research community.
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
The connections between technology applications of all sorts and human users that are ubiquitous in informal learning and assume a great deal about how the technology is used and how learning takes place. Much of the research in this area has been focused on game design and interaction. This project will examine this interaction involving the use of gestures that represent how individuals work with systems and large data sets that represent complex systems like the oceans, to understand how basic elements of a project with a 3-D type of design might enhance the user experience and increase the utility and learning that takes place by understanding the cognitive elements of these game like interactions in specific STEM related settings like museums.
This exploratory pathways project will investigate the use of interactive, gesture-enabled, multi-touch spheres for teaching about ocean systems in science centers and museums. The gesture-enabled aspect of the project will improve on interactive table-top installations which can frustrate users who use unexpected gestures and receive no response leading to brief interaction and abandonment without significant interaction or learning. The project will investigate ways in which unsupported gestures would still produce a system response which would encourage the user to remain at the installation and continue to investigate. The effect of multiple gestures will be supported by using natural mappings between gestures and interactions with the on-sphere data.
The project investigates theories of embodied cognition that support the notion that by engaging with global-scale datasets on a spherical display more effectively models the earth in a non-distorted manner and therefore will be more natural and allow users to develop a more accurate conceptual model of how data relates to itself and the globe. In this way, the project shares some aspects of understanding about learning through game play. The sphere will not be a fully developed game but will share characteristics of game play.
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.
Citizen science engages members of the public in science. It advances the progress of science by involving more people and embracing new ideas. Recent projects use software and apps to do science more efficiently. However, existing citizen science software and databases are ad hoc, non-interoperable, non-standardized, and isolated, resulting in data and software siloes that hamper scientific advancement. This project will develop new software and integrate existing software, apps, and data for citizen science - allowing expanded discovery, appraisal, exploration, visualization, analysis, and reuse of software and data. Over the three phases, the software of two platforms, CitSci.org and CyberTracker, will be integrated and new software will be built to integrate and share additional software and data. The project will: (1) broaden the inclusivity, accessibility, and reach of citizen science; (2) elevate the value and rigor of citizen science data; (3) improve interoperability, usability, scalability and sustainability of citizen science software and data; and (4) mobilize data to allow cross-disciplinary research and meta-analyses. These outcomes benefit society by making citizen science projects such as those that monitor disease outbreaks, collect biodiversity data, monitor street potholes, track climate change, and any number of other possible topics more possible, efficient, and impactful through shared software.
The project will develop a cyber-enabled Framework for Advancing Buildable and Reusable Infrastructures for Citizen Science (Cyber-FABRICS) to elevate the reach and complexity of citizen science while adding value by mobilizing well-documented data to advance scientific research, meta-analyses, and decision support. Over the three phases of the project, the software of two platforms, CitSci.org and CyberTracker, will be integrated by developing APIs and reusable software libraries for these and other platforms to use to integrate and share data and software. Using participatory design and agile methods over four years, the project will: (1) broaden the inclusivity, accessibility, and reach of citizen science; (2) elevate the value and rigor of citizen science software and data; (3) improve interoperability, usability, scalability and sustainability of citizen science software and data; and (4) mobilize data to allow cross-disciplinary research and meta-analyses. These outcomes benefit society by making citizen science projects and any number of other possible topics more possible, efficient, and impactful through shared software and data. Adoption of Cyber-FABRICS infrastructure, software, and services will allow anyone with an Internet or cellular connection, including those in remote, underserved, and international communities, to contribute to research and monitoring, either independently or as a team. This project is also being supported 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:
Gregory NewmanLouis LiebenbergStacy LynnMelinda Laituri