Mid-America Science Museum will implement a professional development program for its education staff and those from member museums of the Arkansas Discovery Network. Museum staffers will participate in a series of three day-long workshops on robotics, app development, and microprocessors. Workshop follow-up will be in the form of strategically scheduled internet-based meetings, an online community, and various methods of evaluation. The program will provide up-to-date professional development and training in newer technologies for educators in the museum and from across Arkansas. Training will encourage these educators to develop their own activities to increase audience engagement and use modern technology to create powerful professional development opportunities for teachers. The project will advance the museum's strategic goal of being a leader in informal science education and creating professional development opportunities for museum educators across the region.
We explored the potential of science to facilitate social inclusion with teenagers who had interrupted their studies before the terms set for compulsory education. The project was carried out from 2014 to 2018 within SISSA (International School for Advanced Studies), a scientific and higher education institution in physics, mathematics and neurosciences, and was focused on the production of video games using Scratch. The outcomes are encouraging: through active engagement, the participants have succeeded in completing complex projects, taking responsibilities and interacting with people
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Simona CerratoFrancesca RizzatoLucia TealdiElena Canel
This article reflects the results of the project “Open Access Statistics”, which was designed to collect standardized usage figures for scientific documents. The data gathered were primarily intended to provide impact values based on document usage for Open Access documents as these were excluded from databases used to provide citation based impact scores. The project also planned the implementation of more sophisticated procedures such as network analyses, but was confronted with complex legal requirements.
This commentary introduces a preliminary conceptual framework for approaching putative effects of scholarly online systems on collaboration inside and outside of academia. The first part outlines a typology of scholarly online systems (SOS), i.e., the triad of specialised portals, specialised information services and scholarly online networks which is developed on the basis of nine German examples. In its second part, the commentary argues that we know little about collaborative scholarly community building by means of SOS. The commentary closes with some remarks on further research questions
Participants in this study reported a variety of resources used in the past to learn to code in Apex, including online tutorials, one-day classes sponsored by Salesforce, and meet-up groups focused on learning. They reported various difficulties in learning through these resources, including what they viewed as the gendered nature of classes where the men already seemed to know how to code—which set a fast pace for the class, difficulty in knowing “where to start” in their learning, and a lack of time to practice learning due to work and family responsibilities. The Coaching and Learning Group
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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Vassiliki KalogeraAggelos KatsaggelosKevin CrowstonLaura TrouilleJoshua SmithShane LarsonLaura Whyte
This Research Advanced by Interdisciplinary Science and Engineering (RAISE) project is supported by the Division of Research on Learning in the Education and Human Resources Directorate and by the Division of Computing and Communication Foundations in the Computer and Information Science and Engineering Directorate. This interdisciplinary project integrates historical insights from geometric design principles used to craft classical stringed instruments during the Renaissance era with modern insights drawn from computer science principles. The project applies abstract mathematical concepts toward the making and designing of furniture, buildings, paintings, and instruments through a specific example: the making and designing of classical stringed instruments. The research can help instrument makers employ customized software to facilitate a comparison of historical designs that draws on both geometrical proofs and evidence from art history. The project's impacts include the potential to shift in fundamental ways not only how makers think about design and the process of making but also how computer scientists use foundational concepts from programming languages to inform the representation of physical objects. Furthermore, this project develops an alternate teaching method to help students understand mathematics in creative ways and offers specific guidance to current luthiers in areas such as designing the physical structure of a stringed instrument to improve acoustical effect.
The project develops a domain-specific functional programming language based on straight-edge and compass constructions and applies it in three complementary directions. The first direction develops software tools (compilers) to inform the construction of classical stringed instruments based on geometric design principles applied during the Renaissance era. The second direction develops an analytical and computational understanding of the art history of these instruments and explores extensions to other maker domains. The third direction uses this domain-specific language to design an educational software tool. The tool uses a calculative and constructive method to teach Euclidean geometry at the pre-college level and complements the traditional algebraic, proof-based teaching method. The representation of instrument forms by high-level programming abstractions also facilitates their manufacture, with particular focus on the arching of the front and back carved plates --- of considerable acoustic significance --- through the use of computer numerically controlled (CNC) methods. The project's novelties include the domain-specific language itself, which is a programmable form of synthetic geometry, largely without numbers; its application within the contemporary process of violin making and in other maker domains; its use as a foundation for a computational art history, providing analytical insights into the evolution of classical stringed instrument design and its related material culture; and as a constructional, computational approach to teaching geometry.
This project is funded by the National Science Foundation's (NSF's) Advancing Informal STEM Learning (AISL) program, which supports innovative research, approaches, and resources for use in a variety of learning settings.
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.
This report summarizes evaluative findings from Computational Thinking in Ecosystems project, and the resulting product, i.e., a functional draft of a game called “The Pack.” Evaluative efforts included gathering feedback from key stakeholders—including members of the design based research (DBR) team members at the New York Hall of Science (NYSCI) along with advisors and project partners— about the game and the DBR process, as well as an independent assessment of the game via feedback from educators and a round of play-testing with youth.
Reconceptualizing STEM + Computing Literacy is funded by the STEM+Computing Partnership (STEM+C) program, which seeks to advance multidisciplinary integration of computing and computational thinking in K-12 science, technology, engineering, and mathematics (STEM) teaching and learning through applied research and development across one or more domains, and broadening participation in computing and computing-related fields. The project will study the integration of computational thinking as part of a new and more contemporary perspective of STEM literacy, and will design, develop, and beta-test a prototype literacy assessment tool that will measure computational thinking literacy along with measures of literacy in other STEM content areas. The tool will be available to the general public as a self-measurement application (App) that can be used by individuals to test their own literacy, and by teachers, schools, and informal educators and organizations to assess literacy development in their students and in their STEM education programs. This transdisciplinary research project will begin the process of creating an innovative approach and tool for measuring literacy that will expand the definition of literacy to include computational skills along with science reasoning. Literacy is an important concept and measurement that has traditionally been used to assess an individual's knowledge of science. This project will explore a broader literacy perspective that incorporates learning derived from out of school and one that incorporates computational skills and thinking as part of a more contemporary perspective of STEM literacy. A prototype web-based App allowing individuals and education organizations to assess literacy levels, and ways to enhance literacy, will be developed and studied. The methodology will be developed using discussions and knowledge from over 60 experts across computing, education, science, social science, and other STEM fields using a Delphi method to engage in reconceptualization of literacy. The hypothesis is that this new STEM+C literacy framework should be structured along four interacting but semi-independent domains: 1) general STEM+C knowledge; 2) self-defined areas of STEM+C knowledge and expertise; 3) attitudes and beliefs related to STEM+C; and 4) the skills and competencies necessary to participate in STEM+C related pursuits and discussions, including measures of modes of STEM+C thinking. Each of these four domains is likely to include numerous sub-domains and associated descriptors, which collectively describe the different aspects of being a STEM+C literate citizen. The application will be designed to provide feedback to individuals on their knowledge, attitudes and skills compared with those of others and suggest ways to enhance and improve their skills and understanding through an embedded feedback mechanism. This project creates public benefit by providing individuals and organizations with a responsive real-time understanding measuring STEM+C literacy, deepening the dialogue about the value of public engagement in science, engineering, technology, math and computing and revealing the dynamic factors that inform STEM+C literacy.
This project tackles the urgent needs of the nation to engage people of all ages in computational thinking and help them learn basic computer science concepts with a unique and innovative approach of structured in-game computer program coding. Researchers will explore the design and development of a 3D puzzle-based game, called May's Journey, in which players solve an environmental maze by using the game's pseudo code to manipulate game objects. The game is designed to teach introductory but foundational concepts of computer programming including abstraction, modularity, reusability, and debugging by focusing players on logic and concepts while asking them to type simple instructions in a simplified programming language designed for novices. The game design in this project differs from today's block-based programming learning approaches that are often too far from actual computer code, and also differs from professional programming languages which are too complex for novices. The game and its embedded programming language learning are designed to be responsive to the progress of the learner throughout the game, transitioning from pseudo code to the embedded programming language itself. Error messages for debugging are also designed to be adaptive to players' behavior in the game. Using extensive log data collected from people playing the game, researchers can study how people learn computer programming. Such knowledge can advance understanding of the learning processes in computer programming education. Additionally, this work emphasizes the use of games as informal learning environments as they are accessible and fun, drawing attention and retention of many learners of different age groups with the potential to change attitudes towards computer programming across different populations. This project is co-funded by the STEM + Computing (STEM+C) program that supports research and development to understand the integration of computing and computational thinking in STEM learning, and the Advancing Informal STEM Learning (AISL) program that funds innovative research, approaches and resources for use in a variety of settings with its overall strategy to enhance learning in informal environments.
The project's formative and summative evaluation methods, including surveys, expert reviews of learners' computer code developed in the game, and interviews, are used to gauge learners' engagement as well as learning. In exploring learning, researchers aim to understand how players build implicit computer science knowledge through gameplay and how that gameplay relates to their performance on external transfer tasks. The project will answer the following three research questions: (1) Can observers reliably detect and label patterns of gameplay that provide evidence of learning or misconceptions regarding the four computer science constructs - abstraction, modularity, debugging and semantics - that learners exhibit playing May's Journey? (2) How does learner's implicit knowledge of these computer science constructs change over time and do those patterns vary by gender and prior programming experiences? (3) Is there a strong correlation between implicit learning measures and transfer of CS concepts: modularity, debugging, semantics, and abstraction? How do these correlations vary across elements of the game? This work will result in several outcomes: game design metaphors tested for their learning and engagement value that can be abstracted and embedded in different games. This project will also contribute patterns and an understanding of how people learn and engage in problem solving using concepts of abstraction, modularity, debugging and semantics. These outcomes will lead to advancement in knowledge in the learning sciences as well as the design of educational games that enrich STEM learning, particularly in programming and computational thinking. In addition, this project will engage female participants and underserved populations through partnering organizations including National Girls Collaborative project.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
The Science Behind Pixar (SBP) exhibition was the product of a collaborative effort among the Museum of Science, Boston (MOS), Pixar Animation Studios, and the Science Museum Exhibit Collaborative (SMEC). The 13,000 square foot exhibition presented the science, math, and computer science behind Pixar Animation Studios’ animated films and innovation. Before entering SBP, visitors watched a five-minute film that oriented them to the exhibition and discussed its main messages. Visitors then interacted with screen-based and physical interactive exhibits, as well as the technical pipeline of the