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.
The Clubhouse Network: A Global Community for Creativity and Achievement, a program of Boston's Museum of Science, will develop, pilot, and evaluate Light it Up! Engaging Young People in Digital Making Activities. Digital making activities combine design, computational thinking, and engineering practices that are all fundamental learning skills for the 21st century. Over the course of six months, the project team will develop a one-day, hands-on workshop that will give museum educators strategies to inspire a more diverse population of middle and high school-aged youth to consider educational and career pathways in STEM fields through engagement with local science centers. The workshop will be implemented twice with a group of 12 educators from regional museums. The museum will use tested evaluation tools to improve the quality and outcomes of the workshops. A successful prototype and evaluation will result in practices that can be adapted by other museums and cultural institutions to better reach young people with digital making activities.
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TEAM MEMBERS:
Gail Breslow
resourceprojectProfessional Development, Conferences, and Networks
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.
This exploratory learning research and design project will study how to use emerging technologies to help document practices in maker-based learning experiences. Despite its established potential for consolidating learning and sense-making, project documentation is often overlooked, not prioritized or seen as burdensome and therefore not integrated into the learning experiences. The project team seeks to understand and address with practice partners the barriers to documentation by systematically exploring how to physically embed and incorporate smart tools and documentation practices into learning environments, specifically creative hands-on learning spaces, like makerspaces. The goal is to understand how to scaffold learners to become more aware, reflective and attentive to their progress towards learning outcomes by embedding supportive tools physically in space as the actions unfold. Making and maker-based learning experiences offer tremendous opportunities to more fully engage diverse learners in STEM education and build a workforce prepared for innovation. Documentation of these learning experiences, both as an authentic practice that professionals engage in as well as an assessment practice for instruction, is often not supported. The project will create open source documentation for solutions and develop supporting case studies, web resources and guides to facilitate easy uptake and adoption of promising approaches.
This proposal will make significant research contributions in three ways: (1) develop and iteratively test a suite of embedded "smart" tools designed to scaffold, manage and trace process documentation practices; (2) study the integration of these tools in formal and informal activities and programs settings and characterize their influence on instruction and the assessment of learning outcomes; (3) establish a set of rubrics based on learner data streams to aid instruction and mark learner progress. Improving documentation practices and the assessment of learning outcomes will advance making as a core STEM educational activity. Through a better understanding of why and how to place networked documentation tools sensitive to space, time and context cues, the threshold for enactment and scaffolded usage can be lowered in a broader range of settings. Ultimately, this exploratory project will not only develop an integrated set of situated documentation tools, but also help us develop hypotheses for how documentation as a mediating process productively supports learning.
The Discovery Research K-12 program (DRK-12) seeks to significantly enhance the learning and teaching of science, technology, engineering and mathematics (STEM) by preK-12 students and teachers, through research and development of innovative resources, models and tools (RMTs). Projects in the DRK-12 program build on fundamental research in STEM education and prior research and development efforts that provide theoretical and empirical justification for proposed projects. The Multimedia Immersion (MI) project is will develop, pilot, and evaluate a nine-week STEM-rich multimedia production course for high school students. MI will make important contributions to the field through its efforts to design and evaluate the promises and challenges of a nine-week multimedia curriculum in multiple urban high schools. The MI course will engage teams of students to develop a personally and socially relevant storyline that guides their use of accessible audio and video technologies to create a five-minute animated video. To develop student STEM experience and provide technical support, the project will provide guidance and learning experiences in engineering (e.g., criteria, constraints, optimization, tradeoffs), science (e.g. sound, light, energy, mechanics) and multimedia technologies (e.g., computer based audio production, video editing and visualizations through animatics (i.e., shooting a succession of storyboards with a soundtrack). animatics).
Because the curriculum situates engineering and science learning in the context of multimedia production, there are natural synergies with several existing high school courses including engineering design, audio/video media production, and multimedia technology. Although these courses are typically electives in high school, developing a 5-minute animated short on a topic of interest may encourage girls and students from underrepresented groups to select this course over other electives. MI will impact 10 teachers and approximately 250 high school students per year. The project will result in the following resources: nine-week curricular unit (multimedia, science, engineering); assessments to monitor student learning of science, engineering and technology (design logs); and research on changes in student knowledge, interest, and a nine-week curricular unit (multimedia, science, engineering). Project resources will be disseminated to teachers, researchers, and curriculum and professional development providers via conference presentations, publications, and online webinars.
The MI project builds on student familiarity and interest in music, video and technology to promote an: (1) understanding of engineering design and physics and an (2) an appreciation of the fundamental role of STEM in popular culture. Project evaluation will be conducted using student surveys and an examination of work products in conjunction with implementation challenges and successes to generate evidence for the feasibility and utility of a high school multimedia course that explicitly addresses science and engineering learning. Project evaluation will use student design logs as a window into student design processes and conceptual understanding. Student design logs are an essential feature of MI curriculum design. With an appropriate structure, these design logs can inform teaching, afford an opportunity for students to reflect on their own work, and provide evidence of student thinking and learning for assessment purposes. Using student design logs as a window into students? design process and conceptual understanding is an important contribution to the engineering education community which has few options for measuring student knowledge in ways that are consistent with the hands-on, iterative nature of the design process.
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, an NSF INCLUDES Design and Development Launch Pilot, managed by the University of Nevada, Reno, addresses the grand challenge of increasing underrepresentation regionally in the advanced manufacturing sector. Using the state's Learn and Earn Program Advanced Career Pathway (LEAP) as the foundation, science, technology, engineering and mathematics (STEM) activities will support and prepare Hispanic students for the region's workforce in advanced manufacturing which includes partnerships with Truckee Meadows Community College (TMCC), the state's Governor's Office of Economic Development, Charles River Laboratories, Nevada Established Program to Stimulate Competitive Research (Nevada EPSCoR) and the K-12 community.
The expected outcomes from the project will inform the feasibility, expandability and transferability of the LEAP framework in diversifying the state's workforce locally and the STEM workforce nationally. Formative and summative evaluation will be conducted with a well-matched comparison group. Dissemination of project results will be disseminated through the Association for Public Land-Grant Universities (APLU), STEM conferences and scholarly journals.
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TEAM MEMBERS:
David ShintaniJulie EllsworthKarsten HeiseRobert StachlewitzRegina Tempel
The University of Texas at Austin's Texas Advanced Computing Center, Chaminade University of Honolulu (CUH), and the Georgia Institute of Technology will lead this NSF INCLUDES Design and Development Launch Pilot (DDLP) to establish a model for data science preparation of Native Hawaiian and Pacific Islander (NHPI) students at the high school and undergraduate levels. The project is premised on the promise of NHPI communities gaining access to, and the ability to work with, large data sets to tackle emerging problems in the Pacific. Such agency over "big data" sets that are relevant to Pacific issues, and contemporary skills in data science, analytics and visualization have the potential to be transformative for community improvement efforts. The effort has the potential to advance knowledge, instructional pedagogy and practices to improve NHPI high school and undergraduate students performance in and attraction to STEM education and careers.
The project team will work to: 1) Increase interest and proficiency in data science and visualization among NHPI high school and undergraduate students through a summer immersion experience that bridges computation and culture; 2) Build data science capacity at an NHPI serving undergraduate institution (CUH) through creation of a certificate program; and 3) Develop and expand partnerships with other organizations with related goals working with NHPI populations. The month-long summer training for 20 NHPI college students, and five NHPI high school students, takes place at CUH and focuses on data science, visualization, and virtual reality, including working on problem sets that require data science approaches and incorporate geographically, socially- and culturally-relevant research themes.
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TEAM MEMBERS:
Kelly GaitherRosalia Gomez
resourceprojectProfessional Development, Conferences, and Networks
The goal of FLIP (Diversifying Future Leadership in the Professoriate), an NSF INCLUDES Design and Development Launch Pilot, is to address the broadening participation challenge of increasing the diversity of the future leadership in the professoriate in computing at research universities as a way to achieve diversity across the field. According to the 2016 CRA Taulbee Survey, only 4.3% of the tenure-track faculty at PhD-granting universities are from underrepresented minorities. This challenge is important to address because diverse faculty contributes to academia in the following critical ways: serve as excellent role models for a diverse study body, bring diverse backgrounds to the student programs and policies developed by the department, and bring diverse perspectives to the research projects and programs. Further, the focus is on research universities, because in practice, key national leadership roles, such as serving on national committees that impact thefield of computing, often come from research universities.
The shared purpose and broad vision of the FLIP launch pilot is to increase faculty diversity in computing at research universities by increasing the diversity of PhD graduates from the top producers of computing faculty. The focus is on four underrepresented groups in computing: African Americans; Hispanics; Native Americans and indigenous peoples; and Persons with Disabilities. The long-term goal is to pursue this vision through strategic partnerships with those institutions that are the top producers of computing faculty and organizations that focus on diverse students in STEM, as well as partnerships that collectively adopt proven strategies for recruiting, graduating, and preparing a diverse set of doctoral students for academic careers. The purpose of the pilot is to establish a unified approach across the different partners that will build upon proven strategies to develop novel practices for increasing the diversity of the PhD graduates from key institutions, thereby increasing the faculty diversity in computing at research universities. For the pilot, FLIP will focus on recruitment and admissions and professional development for current PhD students.
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TEAM MEMBERS:
Valerie TaylorCharles IsbellJeffrey ForbesUniversity of Chicago
The University of New Hampshire (UNH) NSF INCLUDES Design and Development Launch Pilot project is a collaborative effort with the Community College System of New Hampshire, Advanced Manufacturing (AM) businesses, NH Economic Development, and the University of New Hampshire to address workforce development in the Advanced Manufacturing sector in the state. The Advanced Manufacturing Program (AMP) uses a framework built on the Collective Impact collaboration model that enables AMP partners to innovate, plan, and implement strategies that significantly increase NH's community colleges (CC) as a source for future workers and leaders in AM.
Specifically, this proposal addresses the pressing need for increasing numbers of AM workers through strategies designed to increase the retention of low socioeconomic status (LSES) students in CC STEM degree programs. AMP coordinates four key implementation strategies: 1) Co-requisite remediation within mathematics and quantitative reasoning; 2) Guided Pathways mentorship with "high touch" advising and student guidance resources that combines clearly defined academic pathways leading to 4-year college transfer and job placement; 3) paid work-based learning (WBL) experiences in industry and academic research; and 4) mentor inclusiveness training to prepare the workplace and academic settings to receive LSES students into a supportive climate. Successfully coordinating these four components through the process of Collective Impact collaboration will lead to a flexible and integrated AM workforce pipeline that serves CC AM students, AM industry partners, and the state as a whole. Findings will be disseminated to academic, business, and government stakeholders in NH, the region, and nationally to inform and improve broadening participation initiatives.
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TEAM MEMBERS:
Palligarnai VasudevanStephen HaleBrad KinseyLeslie BarberMelissa Aikens