The Council for Opportunity in Education, in collaboration with TERC, seeks to advance the understanding of social and cultural factors that increase retention of women of color in computing; and implement and evaluate a mentoring and networking intervention for undergraduate women of color based on the project's research findings. Computing is unique because it ranks as one of the STEM fields that are least populated by women of color, and because while representation of women of color is increasing in nearly every other STEM field, it is currently decreasing in computing - even as national job prospects in technology fields increase. The project staff will conduct an extensive study of programs that have successfully served women of color in the computing fields and will conduct formal interviews with 15 professional women of color who have thrived in computing to learn about their educational strategies. Based on those findings, the project staff will develop and assess a small-scale intervention that will be modeled on the practices of mentoring and networking which have been established as effective among women of color who are students of STEM disciplines. By partnering with Broadening Participation in Computing Alliances and local and national organizations dedicated to diversifying computing, project staff will identify both women of color undergraduates to participate in the intervention and professionals who can serve as mentors to the undergraduates in the intervention phase of the project. Assisting the researchers will be a distinguished Advisory Board that provides expertise in broadening the representation of women of color in STEM education. The external evaluator will provide formative and summative assessments of the project's case study data and narratives data using methods of study analysis and narrative inquiry and will lead the formative and summative evaluation of the intervention using a mixed methods approach. The intervention evaluation will focus on three variables: 1) students' attitudes toward computer science, 2) their persistence in computer science and 3) their participant attitudes toward, and experiences in, the intervention.
This project extends the PIs' previous NSF-funded work on factors that impact the success of women of color in STEM. The project will contribute an improved understanding of the complex challenges that women of color encounter in computing. It will also illuminate individual and programmatic strategies that enable them to participate more fully and in greater numbers. The ultimate broader impact of the project should be a proven, scalable model for reversing the downward trend in the rates at which women of color earn bachelor's degrees in computer science.
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
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
The “Fourth Industrial Revolution” is transforming the world of work. Just as it happened with the technologies of the steam, electricity and computer revolutions, digital technologies are now becoming pervasive and reshaping all parts of the global economy. The computing industry’s rate of job creation in the U.S. is now three times the U.S. national average. This rapid expansion of the computing workforce means that computing skills – with coding at the core – are the most sought-after skills in the American job market.
Yet amid this boom, research by Accenture and Girls Who Code shows
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Accenture ResearchKate Harrison
resourceprojectProfessional Development, Conferences, and Networks
A partnership of institutions and organizations from public and private sectors, all with an established record in advancing Hispanics in higher education, will form a networked community across regions of the United States with significant Hispanic populations to collectively adapt and adopt proven practices and apply them throughout the higher education system of two-year colleges and baccalaureate-, master's-, and doctorate-granting universities. The partnership builds on the successful NSF-funded Computing Alliance of Hispanic-Serving Institutions (CAHSI) that has emerged as a significant pipeline of new recruits into computing graduate studies, industry, and the professoriate throughout the nation. Even through the Hispanic population has reached 17% nationally, a mere 4% STEM Master's and 3% STEM doctorate degrees are awarded nationwide to Hispanics in 2012-2013. The desperate need to reach parity is clear. The shared purpose and bold vision of the effort is to achieve parity in the number of Hispanics who complete computation-based graduate studies. The focus will be on targeting the pool of talented students at Hispanic-Serving Institutions (HSIs) who, for various reasons, do not choose to continue on STEM educational and career pathways. The efforts will focus on transitioning Hispanic students from associate degree programs to baccalaureate programs, and from baccalaureate programs (regardless of where they began their studies) to completion of graduate degrees.
The project will establish a common agenda that guides the vision and strategy for collective impact, conduct data collection to longitudinally track student movement across campuses, and launch a multi-site pilot to test feasibility of the full-scale plan and process for change. While prior research has identified strategies for increasing graduate program completion rates for underrepresented minorities, little attention has been paid to the role of HSIs in reducing attrition. Attention to HSIs is a critical element in developing successful pathways to STEM careers. The networked community will involve social scientists across the different regions in research on Hispanic graduate program completion, to complement existing research on undergraduate completion. Developing a comprehensive, scalable model for cross-institutional advancement of students, in particular the combination of a bilingual and bicultural student body with unique needs, is critical to grow the STEM pipeline. Through a pilot, the project will engage two-year colleges and universities to begin the initial investigation on the impact of building strong student identity, student belonging, advocacy, and preparation on accelerating the number of students entering, persisting in the major, and considering, entering, and ultimately completing graduate studies in computational areas.
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TEAM MEMBERS:
Ann GatesMarjorie ZatzMohsen BeheshtiEnrico PontelliAaron Velasco
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.
As part of an overall strategy to enhance learning within maker contexts in formal and informal environments, the Innovative Technology Experiences for Students and Teachers (ITEST) and Advancing Informal STEM Learning (AISL) programs partnered to support innovative models for making in a variety of settings through the Enabling the Future of Making to Catalyze New Approaches in STEM Learning and Innovation Dear Colleague Letter. This Early Concept Grant for Exploratory Research (EAGER) will test an innovative approach to bringing making from primarily informal out-of-school contexts into formal science classrooms. While the literature base to support the positive outcomes and impacts of design-based making in informal settings at the K-12 level is emerging, to date, minimal studies have investigated the impacts of making design principles within formal contexts. If successful, this project would not only add to this gap in the literature base but would also present a novel model for bridging the successful engineering design practices of making and tinkering primarily found in informal science education into formal science education classrooms. The model would also demonstrate an innovative, highly interactive way to engage high school students and their teachers in engineering based design principles with immediate real-world applications, as the scientific instruments developed in this project could be integrated directly into science classrooms at relatively minimal costs.
Through a multi-phased design and implementation model, high school students and their teachers will engage deeply in making design principles through the design and development of their own scientific instruments using Arduino-compatible hardware and software. The first phase of the project will reflect a more traditional making experience with up to twenty high school students and their teachers participating in an after-school design making club, in this case, focused on the development and testing of scientific instrument prototypes. During the second phase of the project, the first effort to transpose the after school making experience to a more formalized experience will be tested with up to eight students selected to participate in two week summer research internships focused on scientific instrument design and development through making at Northwestern University. A two-day summer teacher workshop will also be held for high school teachers participating in the subsequent pilot study. The collective insights gleaned from the after school program, student internships, and teacher workshop will culminate to inform the full implementation of the formal classroom pilot study. The third and final phase will coalesce months of iterative, formative research, design and development, resulting in a comprehensive pilot investigation in up to seven high school physics classrooms.
Using a multi-phased, mixed methods exploratory design-based research approach, this 18-month EAGER will explore several salient research questions: (a) How and to what extent does the design & making of scientific instrumentation serve as useful tasks for learning important science and engineering knowledge, practices, and epistemologies? (b) How engaging is this making activity to learners of diverse abilities and prior interests? What can be generalized to other types of making activities? (c) How accessible is the Arduino hardware and coding environment to learners? What combination of hardware and software materials and tools best support accessibility and learning in this type of digital making activity? and (d) What types of scaffolding (for students and teachers) are required to support the effective use of maker materials and activities in a classroom setting? Structured interviews, artifacts, video recordings from visor cameras, student design logs, logfiles, and ethnographic field notes will be employed to garner data and address the research questions. Given the early stage of the proposed research, the dissemination of the findings will be limited to a few select journals, teacher forums and workshops, and professional conferences.
This EAGER is well-poised to directly impact up to 125 high school physics students (average= 25 students/class), approximately 7 high school physics teachers, 6-8 high school summer interns, nearly 20 high school students participating in the after-school design making club, and indirectly many more. The results of this EAGER could provide the basis and evidence needed to support a more robust, expanded future investigation to further substantiate the findings and build the case for similar efforts to bring making into formal science education contexts.
Computer Science (CS) education at the middle school level using educational games has seen recent growth and shown promising results. Typically these games teach the craft of programming and not the perspectives required for computational thinking, such as abstraction and algorithm design, characteristic of a CS curriculum. This research presents a game designed to teach computational thinking via the problem of minimum spanning trees to middle school students, a set of evaluation instruments, and the results of an experimental pilot study. Results show a moderate increase in minimum spanning