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
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.
The Young Developers program is an after school program conceptualised and run by The P-STEM Foundation. It introduces computer programming and design concepts to high school age students from South African historically disadvantaged communities, where the majority of students have had little or no interaction with computers. Young Developers uses Self Organised Learning Methodology and involves introducing a series of increasingly complex challenges / questions that the participants have to collaboratively solve. The first module is run in Scratch with the final objective being the creation of a racing car game. The second module is run in Python using Turtle graphics with an objective of creating an animation. This program runs as pods in each of the communities that the P-STEM foundation works in. Each pod has up to 30 teens from the age of 10 to 18. Each pod is peer led and peer driven, and the pace of learning is determined by the participants. In 2015, we would also like to introduce national competitions which pods participate in against other pods.
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.
As part of its overall strategy to enhance learning in informal environments, the Advancing Informal STEM Learning (AISL) program funds innovative resources for use in a variety of settings. Nationally, the US has a shortage of computer scientists; a big part of this problem is that girls are discouraged from learning computer science at a very young age. This project tries to address this problem by creating a videogame specifically oriented towards getting middle school girls interested in learning computer science concepts outside traditional programming classes. Based on evidence that stories provide a compelling way to present complicated technical subjects and that girls in particular respond to technology careers as a way to help others, the project is building a videogame called "Gram's House" in which social workers intend to move a fictional grandmother to a retirement home unless the player can outfit her home with sufficient technology for her to remain independent. Solving puzzles in the game requires learning core computer science concepts. Research studies will be conducted to determine whether the videogame is effective at getting girls interested in computer science, at teaching computer science concepts, and whether using stories makes videogames more effective for learning. This project based on an earlier successful prototype uses an iterative research-based design process including paper prototyping, playtesting, and focus groups (N=20) to create age appropriate activities, based on the CS Unplugged series, that support learning concepts from the Data, Internet, Algorithms, and Abstraction sections of the high-school level CS Principles curriculum. A quantitative, quasi-experimental design will be used to determine the overall effectiveness of teaching CS concepts under three types of game conditions: (a) games alone, (b) games with fictional settings, and (c) games with stories. A novel assessment instrument will be developed to assess content learning and qualitative observation using a standard observation protocol will be used to gauge interest and engagement. 70-80 middle school girls will be recruited for afterschool participation in the study in two states. As part of the dissemination efforts, a facilitator's guide, rule book, and materials such as maps and storyboards will be created and shared with the game. In addition, a workshop for computer science and other teachers who are interested in using games to teach CS concepts will be conducted.
Northeastern University will design, test, and study GrACE, a procedurally generated puzzle game for teaching computer science to middle school students, in partnership with the Northeastern Center for STEM Education and the South End Technology Center. The Principal Investigators will study the effect of computer generated games on students' development of algorithmic and computational thinking skills and their change of perception about computer science through the game's gender-inclusive, minds-on, and collaborative learning environment. The teaching method has potential to significantly advance the state of the art in both game-based learning design and yield insights for gender-inclusive teaching and learning that could have broad impact on advancing the field of computer science education. Development and evaluation of GrACE will consist of two, year-long research phases, each with its own research question. The first, design and development, phase will focus on how to design a gender-inclusive, educational puzzle game that fosters algorithmic thinking and positive attitude change towards computer science. The content generator will be created using Answer Set Programming, a powerful approach that involves the declarative specification of the design space of the puzzles. The second phase will be an evaluation that studies, by means of a mixed-methods experimental design, the effectiveness of incorporating procedural content generation into an educational game, and specifically whether such a game strategy stimulates and improves minds-on, collaborative learning. Additionally, the project will explore two core issues in developing multiplayer, collaborative educational games targeted at middle school students: what typical face-to-face interactions foster collaborative learning, and what gender differences exist in how students play and learn from the game. The project will reach approximately 100 students in the Boston area, with long-term goals of reaching students worldwide, once the game has been tested with a local audience. Results of the project will yield a new educational puzzle game that can teach algorithmic thinking and effect attitude change regarding computer science. Through the process of creating a gender-inclusive game to teach computer science, it will provide guidelines for future educational game projects. Beyond these individual project deliverables, it will improve our understanding of the potential for procedural content generation to transform education, through its development of a new technique for generating game content based on supplying educational objectives.
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TEAM MEMBERS:
Northeastern UniversityGillian SmithCasper Harteveld