Thanks, on the one hand, to the extraordinary availability of colossal textual archives and, on the other hand, to advances in computational possibilities, today the social scientist has at their disposal an extraordinary laboratory, made of millions of interacting subjects and billions of texts. An unprecedented, yet challenging, opportunity for science. How to test, corroborate models? How to control, interpret and validate Big Data? What is the role of theory in the universe of patterns and statistical correlations? In this article, we will show some general characteristics of the use of
Computational social science represents an interdisciplinary approach to the study of reality based on advanced computer tools. From economics to political science, from journalism to sociology, digital approaches and techniques for the analysis and management of large quantities of data have now been adopted in several disciplines. The papers in this JCOM commentary focus on the use of such approaches and techniques in the research on science communication. As the papers point out, the most significant advantages of a computational approach in this sector include the chance to open up a range
Lack of diversity in science and engineering education has contributed to significant inequality in a workforce that is responsible for addressing today's grand challenges. Broadening participation in these fields will promote the progress of science and advance national health, prosperity and welfare, as well as secure the national defense; however, students from underrepresented groups, including women, report different experiences than the majority of students, even within the same fields. These distinctions are not caused by the students' ability, but rather by insufficient aspiration, confidence, mentorship, instructional methods, and connection and relevance to their cultural identity. The long-term vision of this project is to amplify the impact of a successful broadening participation model at the University of Maine, the Stormwater Research Management Team (SMART). This program trains students and mentors in using science and engineering skills and technology to research water quality in their local watershed. Students engage in numerous science and technology fields: engineering design, data acquisition, analysis and visualization, chemistry, environmental science, biology, and information technology. Students also connect with a diversity of professionals in water and engineering in government, private firms and non-profits. SMART has augmented the traditional science and engineering classroom by engaging students in guided mentored apprenticeships that address community problems.
Technical
This pilot project will form a collaborative and define a strategic plan for scale-up to a national alliance to increase the long-term success rate of underrepresented minority students in science, engineering, and related fields. The collaborative of multiple and varied organizations will align to collectively contribute time and resources to a pre-college educational pathway. There are countless isolated programs that offer short-term interventions for underrepresented and minority students; however, there is lack of organizational coordination for aligning current program offerings, sharing best practices, research results or program outcomes along the education to workforce pathway. The collaborative activities will focus on the transition grades (e.g., 4-5, 8, and high school) and emphasize relationships among skills, confidence, culture and future careers. Collaborative partners will establish a centralized infrastructure in each location to coordinate recruiting of invested community leaders, educators, and parents, around a common agenda by designing, deploying and continually assessing a stormwater-themed project that addresses their location and demographic specific needs. This collaborative community will consist of higher education faculty and students, K-12 students, their caregivers, mentors, educators, stormwater districts, state and national environmental protection agencies, departments of education, and other for-profit and non-profit organizations. The collaborative will address the need for research on mechanisms for change, collaboration, and negotiation regarding the greater participation of under-represented groups in the science and technology workforce.
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TEAM MEMBERS:
Mohamed MusaviVenkat BhethanabotlaCary JamesVemitra WhiteLola Brown
The Mississippi Alliance for Women in Computing (MAWC) project will identify factors that influence and motivate female students and female African American students in Mississippi to enroll and persist in an undergraduate engineering- or science-based computing major. There is a particular need for programming that is inclusive of women and women of color who are from the southern region of the United States. These students typically have less access to extracurricular activities that encourage computing, and are less likely to visualize themselves in a computing major or career. This proposed research is to help girls to know that computer science exists and what jobs in computer science are available with a degree in computer science. A rich environment exists in Mississippi for an alliance focused on building co-curricular and mentorship opportunities. A scalable pipeline model, expandable to a Southern Alliance for Women in Computing (SAWC), will be developed with three major objectives: to attract women and women of color to computing, to improve retention rates of women in undergraduate computing majors, and to help postsecondary women make the transition to the computing workforce. Activities to support these objectives include: scaling the National Center for Women and Information Technology Aspirations in Computing award program in Mississippi, expanding scholarships for Aspirations winners, expanding student-led computing outreach programs, establishing a Mississippi Black Girls Code chapter, informing and collaborating with the Computer Science for Mississippi initiative, creating a summer bridge and living-learning community for women in computing majors, and increasing professional development opportunities for women in computing through conferences, lunch and learn meetings, job shadowing, and internships.
The project will analyze whether the co-curricular activities of MAWC lead to computing self-efficacy and ultimately female students selecting to pursue and persist in computing majors and careers. In order to understand student participation and efficacy changes, data collection for this research will be through demographic and background surveys administered to women entering an undergraduate engineering- or science-based computing major at a university in Mississippi and student surveys and evaluations in MAWC-sponsored programs. Using discriminate analysis methods, specific research questions to be addressed are: 1) Which pre-collegiate experiences influenced them to enroll, 2) Which stakeholders influenced these girls in their decision-making process, and 3) What programs are effective in impacting their persistence in the major. Predictor variables for each respective research question are: pre-collegiate experiences, stakeholders, and programs. Outcome variables are: (a) a female undergraduate student with no involvement with MAWC programming, (b) MAWC activity participant, or (c) a MAWC participant having graduated with a bachelor?s degree in a STEM major. Results will complement published longitudinal research on the gendered and raced dimensions of computing literacy acquisition in Mississippi as well as research on effective CS role model programming.
Although major growth in engineering and computing jobs is expected in the next 10 years, students are not majoring in sufficient numbers to meet this demand. These impending workforce demands cannot be met without developing the skills of racial and ethnic minorities: however, Hispanics and Black/African Americans make up only a small percentage of doctoral students in the United States. The goal of the Consortium of Minority Doctoral Scholars (CMDS) Design and Development Launch Pilot is to broaden the participation of minorities in these fields. This pilot project will create a data portal that will allow the research team to study and understand the efficacy of various mentoring strategies that might be piloted across institutions and minority doctoral scholars programs.
Part II
The Consortium of Minority Doctoral Scholars (CMDS) will unite three of the nation's oldest and most prominent minority doctoral scholars programs (GEM, SREB and McKnight); organizations with a long history of impact in increasing the numbers of minorities obtaining advanced degrees. The CMDS Design and Development Launch Pilot will conduct extensive studies using data from these three programs. The research team will conduct a mixed method analysis of the data to discover commonalities and distinctions about the three programs' mentoring efforts as compared to students not involved in the three programs. This will result in a data-driven strategy for researching the efficacy of mentoring programs that can be applied across the three CMSD member and other minority doctoral scholars programs. By utilizing data from successful programs to pinpoint effective mentoring strategies, the project will create opportunities for larger numbers of minorities to be successful. This approach has implications not only with respect to equity and access, but also the development of a workforce that will drive future advances.
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TEAM MEMBERS:
Juan GilbertShaundra DailyJerlando Jackson
The Colleges of Science & Engineering and Graduate Education, and the Metro Academies College Success Program (Metro) at San Francisco State University in partnership with San Francisco Unified School District and the San Francisco Chamber of Commerce develop an integrated approach for computing education that overcomes obstacles hampering broader participation in the U.S. science, technology, engineering and mathematics (STEM) workforce. The partnership fosters a more diverse and computing-proficient STEM workforce by establishing an inclusive education approach in computer science (CS), information technology, and computer engineering that keeps students at all levels engaged and successful in computing and graduates them STEM career-ready.
Utilizing the collective impact framework maximizes the efficacy of existing regional organizations to broaden participation of groups under-educated in computing. The collective impact model establishes a rich context for organizational engagement in inclusive teaching and learning of CS. The combination of the collective impact model of social agency and direct engagements with communities yields unique insights into the views and experiences of the target population of students and serves as a platform for national scalable networks.
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TEAM MEMBERS:
Keith BowmanIlmi YoonLarry HorvathEric HsuJames Ryan
This INSPIRE project addresses the issue of high volume hydraulic fracturing, also called fracking, and its effects on ground water resources. Fracking allows drillers to extract natural gas from shale deep within the earth. Methane gas sometimes escapes from shale gas wells and can contaminate water resources or leak into the atmosphere where it contributes to greenhouse gas emissions. Monitoring for these potential leaks is difficult because methane is also released into aquifers naturally, and because monitoring is time- and resource-intensive. Such subsurface leakage may also be relatively rare. This project seeks to improve overall understanding of the impacts of natural gas drilling using both advances in computer science and geoscience, and to teach the public about such impacts. The project will elucidate both the effects of human activities such as shale gas development as well as natural processes which release methane into natural waters. Results of the proposed research will lead to a better understanding of water quality in areas of shale-gas development and will highlight problems and potentially problematic management practices. The research will advance both the fields of geoscience and computer science, will train interdisciplinary graduate students, and involve citizen scientists in collecting data and understanding environmental data analysis.
The project combines new hydro-geochemical strategies and data mining approaches to study the release of methane into streams and ground waters. For example, researchers will explore how to analyze the heterogeneous spatial data that describe distributions of methane concentrations in natural waters. The objectives of this project are to i) transform the ability to measure methane in streams; ii) train citizen scientists to work with project scientists to sample streams in an area of shale-gas development and publish large-volume datasets of methane in natural waters and aquifers; iii) innovate data mining and machine learning methods for environmental data to identify anomalous spots with potential leakage; iv) run field campaigns to measure methane concentrations and isotopic signatures of water samples in these spots; v) foster dialogue among nonscientists, consultants, university scientists, members of the gas industry, government agencies, and nonprofit organizations in and beyond the target region. Toward this end, the team will host workshops aimed to build dialogue among stakeholders and will release data analytic software for environmental measurements to benefit a broader research community.
This is an Early-concept Grant for Exploratory Research supporting research in Smart and Connected Communities. The research supported by the award is collaborative with research at the University of Colorado. The researchers are studying the use of technologies to enable communities to connect youth and youth organizations to effectively support diverse learning pathways for all students. These communities, the youth, the youth organizations, formal and informal education organizations, and civic organizations form a learning ecology. The DePaul University researchers will design and implement a smart community infrastructure in the City of Chicago to track real-time student participation in community STEM activities and to develop mobile applications for both students and adults. The smart community infrastructure will bring together information from a variety of sources that affect students' participation in community activities. These include geographic information (e.g., where the student lives, where the activities take place, the student transportation options, the school the student attends), student related information (e.g., the education and experience background of the student, the economic status of the student, students' schedules), and activity information (e.g., location of activity, requirements for participation). The University of Colorado researchers will take the lead on analyzing these data in terms of a community learning ecologies framework and will explore computational approaches (i.e., recommender systems, visualizations of learning opportunities) to improve youth exploration and uptake of interests and programs. These smart technologies are then used to reduce the friction in the learning connection infrastructure (called L3 for informal, formal, and virtual learning) to enable the student to access opportunities for participation in STEM activities that are most feasible and most appropriate for the student. Such a flexible computational approach is needed to support the necessary diversity of potential recommendations: new interests for youth to explore; specific programs based on interests, friends' activities, or geographic accessibility; or programs needed to "level-up" (develop deeper skills) and complete skills to enhance youths' learning portfolios. Although this information was always available, it was never integrated so it could be used to serve the community of both learners and the providers and to provide measurable student learning and participation outcomes. The learning ecologies theoretical framework and supporting computational methods are a contribution to the state of the art in studying afterschool learning opportunities. While the concept of learning ecologies is not new, to date, no one has offered such a systematic and theoretically-grounded portfolio of measures for characterizing the health and resilience of STEM learning ecologies at multiple scales. The theoretical frameworks and concepts draw together multiple research and application domains: computer science, sociology of education, complexity science, and urban planning. The L3 Connects infrastructure itself represents an unprecedented opportunities for conducting "living lab" experiments to improve stakeholder experience of linking providers to a single network and linking youth to more expanded and varied opportunities. The University of Colorado team will employ three methods: mapping, modeling, and linking youth to STEM learning opportunities in school and out of school settings in a large urban city (Chicago). The recommender system will be embedded into youth and parent facing mobile apps, enabling the team to characterize the degree to which content-based, collaborative filtering, or constraint based recommendations influence youth actions. The project will result in two measurable outcomes of importance to key L3 stakeholder groups: a 10% increase in the number of providers (programs that are part of the infrastructure) in target neighborhoods and a 20% increase in the number of youth participating in programs.
This is an Early-concept Grant for Exploratory Research supporting research in Smart and Connected Communities. The research supported by the award is collaborative with research at DePaul University. The researchers are studying the use of technologies to enable communities to connect youth and youth organizations to effectively support diverse learning pathways for all students. These communities, the youth, the youth organizations, formal and informal education organizations, and civic organizations form a learning ecology. The DePaul University researchers will design and implement a smart community infrastructure in the City of Chicago to track real-time student participation in community STEM activities and to develop mobile applications for both students and adults. The smart community infrastructure will bring together information from a variety of sources that affect students' participation in community activities. These include geographic information (e.g., where the student lives, where the activities take place, the student transportation options, the school the student attends), student related information (e.g., the education and experience background of the student, the economic status of the student, students' schedules), and activity information (e.g., location of activity, requirements for participation). The University of Colorado researchers will take the lead on analyzing these data in terms of a community learning ecologies framework and will explore computational approaches (i.e., recommender systems, visualizations of learning opportunities) to improve youth exploration and uptake of interests and programs. These smart technologies are then used to reduce the friction in the learning connection infrastructure (called L3 for informal, formal, and virtual learning) to enable the student to access opportunities for participation in STEM activities that are most feasible and most appropriate for the student. Such a flexible computational approach is needed to support the necessary diversity of potential recommendations: new interests for youth to explore; specific programs based on interests, friends' activities, or geographic accessibility; or programs needed to "level-up" (develop deeper skills) and complete skills to enhance youths' learning portfolios. Although this information was always available, it was never integrated so it could be used to serve the community of both learners and the providers and to provide measurable student learning and participation outcomes. The learning ecologies theoretical framework and supporting computational methods are a contribution to the state of the art in studying afterschool learning opportunities. While the concept of learning ecologies is not new, to date, no one has offered such a systematic and theoretically-grounded portfolio of measures for characterizing the health and resilience of STEM learning ecologies at multiple scales. The theoretical frameworks and concepts draw together multiple research and application domains: computer science, sociology of education, complexity science, and urban planning. The L3 Connects infrastructure itself represents an unprecedented opportunities for conducting "living lab" experiments to improve stakeholder experience of linking providers to a single network and linking youth to more expanded and varied opportunities. The University of Colorado team will employ three methods: mapping, modeling, and linking youth to STEM learning opportunities in school and out of school settings in a large urban city (Chicago). The recommender system will be embedded into youth and parent facing mobile apps, enabling the team to characterize the degree to which content-based, collaborative filtering, or constraint based recommendations influence youth actions. The project will result in two measurable outcomes of importance to key L3 stakeholder groups: a 10% increase in the number of providers (programs that are part of the infrastructure) in target neighborhoods and a 20% increase in the number of youth participating in programs.
This one-year Collaborative Planning project seeks to bring together an interdisciplinary planning team of informal and formal STEM educators, researchers, scientists, community, and policy experts to identify the elements, activities, and community relationships necessary to cultivate and sustain a thriving regional early childhood (ages 3-6) STEM ecosystem. Based in Southeast San Diego, planning and research will focus on understanding the needs and interests of young Latino dual language learners from low income homes, as well as identify regional assets (e.g., museums, afterschool programs, universities, schools) that could coalesce efforts to systematically increase access to developmentally appropriate informal STEM activities and resources, particularly those focused on engineering and computational thinking. This project has the potential to enhance the infrastructure of early STEM education by providing a model for the planning and development of early childhood focused coalitions around the topic of STEM learning and engagement. In addition, identifying how to bridge STEM learning experiences between home, pre-k learning environments, and formal school addresses a longstanding challenge of sustaining STEM skills as young children transition between environments.
The planning process will use an iterative mixed-methods approach to develop both qualitative and quantitative and data. Specific planning strategies include the use of group facilitation techniques such as World Café, graphic recording, and live polling. Planning outcomes include: 1) a literature review on STEM ecosystems; 2) an Early Childhood STEM Community Asset Map of southeast San Diego; 3) a set of proposed design principles for identifying and creating early childhood STEM ecosystems in low income communities; and 4) a theory of action that could guide future design and research. This project is funded by the Advancing Informal STEM Learning program, which seeks to advance new approaches to, and evidence-based understanding of, the design and development of STEM learning in informal environments.
Citizen science engages members of the public in science. It advances the progress of science by involving more people and embracing new ideas. Recent projects use software and apps to do science more efficiently. However, existing citizen science software and databases are ad hoc, non-interoperable, non-standardized, and isolated, resulting in data and software siloes that hamper scientific advancement. This project will develop new software and integrate existing software, apps, and data for citizen science - allowing expanded discovery, appraisal, exploration, visualization, analysis, and reuse of software and data. Over the three phases, the software of two platforms, CitSci.org and CyberTracker, will be integrated and new software will be built to integrate and share additional software and data. The project will: (1) broaden the inclusivity, accessibility, and reach of citizen science; (2) elevate the value and rigor of citizen science data; (3) improve interoperability, usability, scalability and sustainability of citizen science software and data; and (4) mobilize data to allow cross-disciplinary research and meta-analyses. These outcomes benefit society by making citizen science projects such as those that monitor disease outbreaks, collect biodiversity data, monitor street potholes, track climate change, and any number of other possible topics more possible, efficient, and impactful through shared software.
The project will develop a cyber-enabled Framework for Advancing Buildable and Reusable Infrastructures for Citizen Science (Cyber-FABRICS) to elevate the reach and complexity of citizen science while adding value by mobilizing well-documented data to advance scientific research, meta-analyses, and decision support. Over the three phases of the project, the software of two platforms, CitSci.org and CyberTracker, will be integrated by developing APIs and reusable software libraries for these and other platforms to use to integrate and share data and software. Using participatory design and agile methods over four years, the project will: (1) broaden the inclusivity, accessibility, and reach of citizen science; (2) elevate the value and rigor of citizen science software and data; (3) improve interoperability, usability, scalability and sustainability of citizen science software and data; and (4) mobilize data to allow cross-disciplinary research and meta-analyses. These outcomes benefit society by making citizen science projects and any number of other possible topics more possible, efficient, and impactful through shared software and data. Adoption of Cyber-FABRICS infrastructure, software, and services will allow anyone with an Internet or cellular connection, including those in remote, underserved, and international communities, to contribute to research and monitoring, either independently or as a team. This project is also being supported by the Advancing Informal STEM Learning (AISL) program, which seeks to advance new approaches to, and evidence-based understanding of, the design and development of STEM learning in informal environments.
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TEAM MEMBERS:
Gregory NewmanLouis LiebenbergStacy LynnMelinda Laituri
This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).
Scientists and researchers from fields as diverse as oceanography and ecology, astronomy and classical studies face a common challenge. As computer power and technology improve, the sizes of data sets available to us increase rapidly. The goal of this project is to develop a new methodology for using citizen science to unlock the knowledge discovery potential of modern, large data sets. For example, in a previous project Galaxy Zoo, citizen scientists have already made major contributions, lending their eyes, their pattern recognition skills and their brains to address research questions that need human input, and in so doing, have become part of the computing process. The current Galaxy Zoo project has recruited more than 200,000 participants who have provided more than 100 million classifications of galaxies from the Sloan Digital Sky Survey. This project builds upon early successes to develop a mode of citizen science participation which involves not only simple "clickwork" tasks, but also involves participants in more advanced modes of scientific thought. As part of the project, a symbiotic relationship with machine learning tools and algorithms will be developed, so that results from citizen scientists provide a rich training set for improving algorithms that in turn inform citizen science modes of participation. The first phase of the project will be to develop a portfolio of pilot projects from astrophysics, planetary science, zoology, and classical studies. The second phase of the project will be to develop a framework - called the Zooniverse - to facilitate citizen scientists. In particular, research and machine-learning communities will be engaged to identify suitable projects and data sets to integrate into Zooniverse.
The ultimate goal with the Zooniverse is to create a sustainable future for large-scale, internet-based citizen science as part of every researcher?s toolkit, exemplifying a new paradigm in computational thinking, tapping the mental resources of a community of lay people in an innovative and complex manner that promises a profound impact on our ability to generate new knowledge. The project will engage thousands of citizens in authentic science tasks leading to a better public understanding of science and also, by the engagement of students, leading to interest in scientific careers.
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TEAM MEMBERS:
Geza GyukPamela GayChristopher LintottMichael RaddickLucy FortsonJohn Wallin