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 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
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.
This project supports the development of technological fluency and understanding of STEM concepts through the implementation of design collaboratives that use eCrafting Collabs as the medium within which to work with middle and high school students, parents and the community. The researchers from the University of Pennsylvania and the Franklin Institute combine expertise in learning sciences, digital media design, computer science and informal science education to examine how youth at ages 10-16 and families in schools, clubs, museums and community groups learn together how to create e-textile artifacts that incorporate embedded computers, sensors and actuators. The project investigates the feasibility of implementing these collaboratives using eCrafting via three models of participation, individual, structured group and cross-generational community groups. They are designing a portal through which the collaborative can engage in critique and sharing of their designs as part of their efforts to build a model process by which scientific and engineered product design and analysis can be made available to multiple audiences. The project engages participants through middle and high school elective classes and through the workshops conducted by a number of different organizations including the Franklin Institute, Techgirlz, the Hacktory and schools in Philadelphia. Participants can engage in the eCrafting Collabs through individual, collective and community design challenges that are established by the project. Participants learn about e-textile design and about circuitry and programming using either ModKit or the text-based Arduino. The designs are shared through the eCrafting Collab portal and participants are required to provide feedback and critique. Researchers are collecting data on learner identity in relation to STEM and computing, individual and collective participation in design and student understanding of circuitry and programming. The project is an example of a scalable intervention to engage students, families and communities in developing technological flexibility. This research and development project provides a resource that engages students in middle and high schools in technology rich collaborative environments that are alternatives to other sorts of science fairs and robotic competitions. The resources developed during the project will inform how such an informal/formal blend of student engagement might be scaled to expand the experiences of populations of underserved groups, including girls. The study is conducting an examination of the new types of learning activities that are multiplying across the country with a special focus on cross-generational learning.
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.
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.
Making Stuff Season Two is designed to build on the success of the first season of Making Stuff by expanding the series content to include a broader range of STEM topics, creating a larger outreach coalition model and a “community of practice,” and developing new outreach activities and digital resources. Specifically, this project created a national television 4-part miniseries, an educational outreach campaign, expanded digital content, promotion activities, station relations, and project evaluation. These project components help to achieve the following goals: 1. To increase public understanding that basic research leads to technological innovation; 2. To increase and sustain public awareness and excitement about innovation and its impact on society; and 3. To establish a community of practice that enhances the frequency and quality of collaboration among STEM researchers and informal educators. These goals were selected in order to address a wider societal issue, and an important element of the overall mission of NOVA: to inspire new generations of scientists, learners, and innovators. By creating novel and engaging STEM content, reaching out to new partners, and developing new outreach tools, the second season of Making Stuff is designed to reach new target audiences including underserved teens and college students crucial to building a more robust and diversified STEM workforce pipeline. Series Description: In this four-part special, technology columnist and best-selling author David Pogue takes a wild ride through the cutting-edge science that is powering a next wave of technological innovation. Pogue meets the scientists and engineers who are plunging to the bottom of the temperature scale, finding design inspiration in nature, and breaking every speed limit to make tomorrow's "stuff" "Colder," "Faster," "Safer," and "Wilder." Making Stuff Faster Ever since humans stood on two feet we have had the basic urge to go faster. But are there physical limits to how fast we can go? David Pogue wants to find out, and in "Making Stuff Faster," he’ll investigate everything from electric muscle cars and the America’s cup sailboat to bicycles that smash speed records. Along the way, he finds that speed is more than just getting us from point A to B, it's also about getting things done in less time. From boarding a 737 to pushing the speed light travels, Pogue's quest for ultimate speed limits takes him to unexpected places where he’ll come face-to-face with the final frontiers of speed. Making Stuff Wilder What happens when scientists open up nature's toolbox? In "Making Stuff Wilder," David Pogue explores bold new innovations inspired by the Earth's greatest inventor, life itself. From robotic "mules" and "cheetahs" for the military, to fabrics born out of fish slime, host David Pogue travels the globe to find the world’s wildest new inventions and technologies. It is a journey that sees today's microbes turned into tomorrow’s metallurgists, viruses building batteries, and ideas that change not just the stuff we make, but the way we make our stuff. As we develop our own new technologies, what can we learn from billions of years of nature’s research? Making Stuff Colder Cold is the new hot in this brave new world. For centuries we've fought it, shunned it, and huddled against it. Cold has always been the enemy of life, but now it may hold the key to a new generation of science and technology that will improve our lives. In "Making Stuff Colder," David Pogue explores the frontiers of cold science from saving the lives of severe trauma patients to ultracold physics, where bizarre new properties of matter are the norm and the basis of new technologies like levitating trains and quantum computers. Making Stuff Safer The world has always been a dangerous place, so how do we increase our odds of survival? In "Making Stuff Safer," David Pogue explores the cutting-edge research of scientists and engineers who want to keep us out of harm’s way. Some are countering the threat of natural disasters with new firefighting materials and safer buildings. Others are at work on technologies to thwart terrorist attacks. A next-generation vaccine will save millions from deadly disease. And innovations like smarter cars and better sports gear will reduce the risk of everyday activities. We’ll never eliminate danger—but science and technology are making stuff safer.
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TEAM MEMBERS:
WGBH Educational FoundationPaula Apsell
Discovering and understanding the temporal evolution of events hidden in text corpora is a complex yet critical task for knowledge discovery. Although mining event dynamics has been an important research topic leading to many successful algorithms, researchers, research and development managers, intelligence analysts and the general public are still in dire need of effective tools to explore the evolutionary trends and patterns. This exploratory project focuses on developing and validating a novel idea called narrative animation. Narrative animation uses animated visualizations to narrate, explore, and share event dynamics conveyed in temporally evolving text collections. Film art techniques are employed to leverage the animated visualizations in information organization and change detection, with the goals of enhancing analytical power and user engagement. A prototype system called CityStories is being developed to generate narrative animations of events in cities derived from web-based text. If this novel, risky research is successful, it is expected to yield fundamental results in narrative animation that can advance the current paradigm in information visualization and visual analytics by developing novel techniques in using animations for presenting and analyzing dynamic abstract data at a large scale. The pilot system CityStories system is expected provide a novel network platform for education, entertainment, and data analytics. It will engage general users such as students, teachers, journalists, bloggers, and many others in web information visualization and study. Results of this research will be disseminated through publications, the World Wide Web, and collaborations with researchers and analysts. The project web site (http://coitweb.uncc.edu/~jyang13/narrativeanimation/narrativeanimation.htm) will include research outcomes, publications, developed software, videos, and datasets for wide dissemination to public.
In this full-scale research and development project, Oregon State University (OSU), Oregon Sea Grant (OSG) and the Hatfield Marine Science Center Visitors Center (HMSCVC) is designing, developing, implementing, researching and evaluating a cyberlaboratory in a museum setting. The cyberlaboratory will provide three earth and marine science learning experiences with research and evaluation interwoven with visitor experiences. The research platform will focus on: 1) a climate change exhibit that will enable research on identity, values and opinion; 2) a wave tank exhibit that will enable research on group dynamics and problem solving in interactive engineering challenges; and 3) remote sensing exhibits that will enable research on visitor interactions through the use of real data and simulations. This project will provide the informal science educaton community with a suite of tools to evaluate learning experiences with emerging technologies using an iterative process. The team will also make available to the informal science community their answers to the following research questions: For the climate change exhibit, "To what extent does customizing content delivery based on real-time visitor input promote learning?" For the wave tank exhibit, "To what extent do opportunities to reflect on and share experiences promote STEM reasoning processes at a build-and-test exhibit?" For the data-sensing exhibit, "Can visitors' abilities to explain or use visualizations be improved by shaping their visual searches of images?" Mixed-methods using interviews, surveys, behavioral instruments, and participant observations will be used to evaluate the overall program. Approximately 60-100 informal science education professionals will discuss and test the viability of the exhibit's evaluation tools. More than 150,000 visitors, along with community members and local middle and high school students, will have the opportunity to participate in the learning experiences at the HMSCVC. This work contributes to the fields of cyberlearning and informal science education. This project provides the informal science education field with important knowledge about learning, customized content delivery and evaluation tools that are used in informal science settings.
In concert with the overall strategy of the Advancing Informal STEM Learning (AISL) program to advance new approaches to, and evidence-based understanding of, the design and development of STEM learning in informal environments, Principal Investigators from Oregon State University, University of Idaho, and University of Texas at Dallas, will study a range of data in online social networks to identify evidence of the long-term impact of informal STEM education. Tracking informal learners over time to understand the impact of informal learning experiences has been a longstanding, daunting, and elusive challenge. Now, with massive amounts of data being shared and stored online, education researchers have an unprecedented opportunity to study such data and apply data analytics and visualization technologies to identify the long-term, cascading effects of informal STEM learning. Research findings will inform the design and development of a data-analysis tool for use by education practitioners to improve STEM learning experiences online, through television and film, and at informal education institutions. An independent external critical review board of learning scientists, computer scientists, engineers, informal STEM education practitioners, participating partners, broadcast media professionals, and policymakers, will ensure a robust evaluation of the research and effectiveness and utility of the data analysis tool to improve practice. A summary report for the field will be written on the scientific and practical reliability and validity of the research and data-analysis model, and the value of the work for audiences beyond informal STEM education practitioners and policymakers. The research is contemporaneously relevant, advancing innovative use of data-mining and data-analysis processes to better understand how informal learners communicate STEM learning experiences and interact with STEM content over time, across a range of social networks. Investigators will research: 1) whether learners who engage in informal STEM education experiences further their learning through discussions and sharing of information in social media networks, 2) which types of data are present in social media that are relevant for understanding the cascading impacts of learning over time, and 3) how learning may evolve independently within shared social networks, which, if discovered, could provide a predictive computational model with implications for significant impact across both formal and informal education. Investigators will employ existing and modified data crawlers to search for key terms and phrases, assess spikes and deformations in posts, queries, and blogs, and experiment with their test data to find which types or configurations of keywords or search terms deliver the most reliable and accurate results. A variety of formats will be explored to test various strategies with participating partners and practitioners. Data will be visualized to represent the following dimensions of learning: a) Interest/Affect, b) Recommendations, c) Understanding/Knowledge-Seeking, and d) Deeper Engagement.