This paper attempts to reframe popular notions of “failure” as recently celebrated in the Maker Movement, Silicon Valley, and beyond. Building on Vossoughi et al.’s 2013 FabLearn publication describing how a focus on iterations/drafts can serve as an equity-oriented pedagogical move in afterschool tinkering contexts, we explore what it means for afterschool youth and educators to persist through unexpected challenges when using an iterative design process in their tinkering projects. More specifically, this paper describes: 1) how young women in a program geared toward increasing equitable
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.
Maker Education scholarship is accumulating increasingly complex understandings of the kinds of learning associated with maker practices along with principles and pedagogies that support such learning. However, even as large investments are being made to spread maker education, there is little understanding of how organizations that are intended targets of such investments learn to develop new maker related educational programs. Using the framework of Expansive Learning, focusing on organizational learning processes resulting in new and unfolding forms of activity, this paper begins to fill
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.
The project team is developing and testing a prototype of a computer science game-based intervention intended for Grade 1 students. The prototype will include physical robots that will be designed and controlled on a game board by students through a blue-tooth enabled smartphone app. The product will include teacher resources and suggestions to facilitate classroom integration. In the Phase I pilot research with 5 classrooms and 150 students, the researchers will examine whether the prototype functions as planned, if teachers are able to implement it with small groups of students, and whether
Keystone Connect Network is a proposed regional broadband network whose purpose is to increase educational opportunities and generate business growth. The backbone of this plan is the Pennsylvania Research and Education Network's (PennREN), a next generation high-speed internet network, managed by KINBER, which educational institutions can use to train their students and create new learning opportunities; and business can create new products and connect with their customers.
For decades, particle physicists have been using open access archives of preprints, i.e. research papers shared before the submission to peer reviewed journals. With the shift to digital archives, this model has proved to be attractive to other disciplines: but can it be exported? In particle physics, archives do not only represent the medium of choice for the circulation of scientific knowledge, but they are central places to build a sense of belonging and to define one's role within the community.