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.
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.
A recent report by the Association for Computing Machinery estimates that by decade's end, half of all STEM jobs in the United States will be in computing. Yet, the participation of women and underrepresented groups in post-secondary computer science programs remains discouragingly and persistently low. One of the most important findings from research in computer science education is the degree to which informal experiences with computers (at many ages and in many settings) shape young people's trajectories through high school and into undergraduate degree programs. Just as early language and mathematics literacy begins at home and is reinforced throughout childhood through a variety of experiences both in school and out, for reasons of diversity and competency, formal experiences with computational literacy alone are insufficient for developing the next generation of scientists, engineers, and citizens. Thus, this CAREER program of research seeks to contribute to a conceptual and design framework to rethink computational literacy in informal environments in an effort to engage a broad and diverse audience. It builds on the concept of cultural forms to understand existing computational literacy practices across a variety of learning settings and to contribute innovative technology designs. As part of its overall strategy to enhance learning in informal environments, the Advancing Informal STEM Learning (AISL) program funds new approaches to and evidence-based understanding of the design and development of STEM learning in these settings. This CAREER program of research seeks to understand the role of cultural forms in informal computational learning experiences and to develop a theoretically grounded approach for designing such experiences for youth. This work starts from the premise that new forms of computational literacy will be born from existing cultural forms of literacy and numeracy (i.e., for mathematical literacy there are forms like counting songs -- "10 little ducks went out to play"). Many of these forms play out in homes between parents and children, in schools between teachers and students, and in all sorts of other place between friends and siblings. This program of study is a three-phased design and development effort focused on key research questions that include understanding (1) how cultural forms can help shape audience experiences in informal learning environments; (2) how different cultural forms interact with youth's identity-related needs and motivations; and (3) how new types of computational literacy experiences based on these forms can be created. Each phase includes inductive research that attempts to understand computational literacy as it exists in the world and a design phase guided by concrete learning objectives that address specific aspects of computational literacy. Data collection strategies will include naturalist observation, semi-structured, and in-depth interviews, and learning assessments; outcome measures will center on voluntary engagement, motivation, and persistence around the learning experiences. The contexts for research and design will be museums, homes, and afterschool programs. This research builds on a decade of experience by the PI in designing and studying computational literacy experiences across a range of learning settings including museums, homes, out-of-school programs, and classrooms. Engaging a broad and diverse audience in the future of STEM computing fields is an urgent priority of the US education system, both in schools and beyond. This project would complement substantial existing efforts to promote in-school computational literacy and, if successful, help bring about a more representative, computationally empowered citizenry. The integrated education plan supports the training and mentoring of graduate and undergraduate students in emerging research methods at the intersection of the learning sciences, computer science, and human-computer interaction. This work will also develop publically available learning experiences potentially impacting thousands of youth. These experiences will be available in museums, on the Web, and through App stores.