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.
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
Increasingly, the prosperity, innovation and security of individuals and communities depend on a big data literate society. Yet conspicuously absent from the big data revolution is the field of teaching and learning. The revolution in big data must match a complementary revolution in a new kind of literacy, through a significant infusion of STEM education with the kinds of skills that the revolution in 21st century data-driven science demands. This project represents a concerted effort to determine what it means to be a big data literate citizen, information worker, researcher, or policymaker; to identify the quality of learning resources and programs to improve big data literacy; and to chart a path forward that will bridge big data practice with big data learning, education and career readiness.
Through a process of inquiry research and capacity-building, New York Hall of Science will bring together experts from member institutions of the Northeast Big Data Innovation Hub to galvanize big data communities of practice around education, identify and articulate the nature and quality of extant big data education resources and draft a set of big data literacy principles. The results of this planning process will be a planning document for a Big Data Literacy Spoke that will form an initiative to develop frameworks, strategies and scope and sequence to advance lifelong big data literacy for grades P-20 and across learning settings; and devise, implement, and evaluate programs, curricula and interventions to improve big data literacy for all. The planning document will articulate the findings of the inquiry research and evaluation to provide a practical tool to inform and cultivate other initiatives in data literacy both within the Northeast Big Data Innovation Hub and beyond.
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
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.
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
Computer science education is rapidly being recognized as essential for all students to develop into successful citizens of the 21st century. A diverse group of stakeholders, including educators, business and industry, policymakers, and parents all agree on the importance of computer science. Significant workforce needs in particular are driving the push for computer science education. In comparison to all other U.S. job categories, computing is projected to have the largest percent growth between 2014 and 2024. And this projected growth may not even entirely capture the full number of
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 a part of its overall strategy to enhance learning in informal environments, the Advancing Informal STEM Learning (AISL) program funds research and innovative resources for use in a variety of settings. This media and technology project will scale up Youth Radio's proven model of STEM education through youth-driven multimedia journalism and related app development using the MIT App Inventor. A new Youth News Network (YNN) will implement a nationwide feeder system of youth reporters and educators using the previously developed and proven STEM curriculum. Previous research and evaluation has demonstrated that this model can engage underserved youth and put them in leadership positions in technological innovation. Key deliverables include the YNN STEM Desk that will produce 15-20 STEM-related stories each year; bootcamps (1-3 day workshops) training youth around the country focusing on app development and media links; and new toolkits providing resources to help with app development, data analysis and other STEM-specific skills. Project partners include MIT Media Lab, National Public Radio, Best Buy's Teen Tech Centers, National Writing Project, Computer Clubhouses, and PBS Learning Media among others.
Over the previous eight years, research and evaluation findings had been used to refine the project. These data served as the foundation for this scale-up project. The research conducted by the investigator and the Scholar-in-Residence in this scale-up uses an embedded ethnographic approach that combines field notes, recorded meetings and discussions, media artifacts, etc.--data that is transcribed and coded for indicators of STEM learning and critical computational literacy. The external summative evaluation will build on prior evidence regarding how this unique model engages youth and impacts their skills in STEM related media and technology.
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TEAM MEMBERS:
Elisabeth SoepEllin O'LearyHarold Abelson
While the term 'failure' brings to mind negative associations, there is a current focus on failure as a driver of innovation and development in many professional fields. It is also emerging from prior research that for STEM professionals and educators, failure plays an important role in designing and making to increase learning, persistence and other noncognitive skills such as self-efficacy and independence. By investigating how youth and educators attend to moments of failure, how they interpret what this means, and how they respond, we will be better able to understand the dynamics of each part of the experience. The research team will be working with youth from urban, suburban and rural settings, students from Title I schools or who qualify for free/reduced-price lunches, those from racial and ethnic minority groups, as well as students who are learning English as a second language. These youth are from groups traditionally underrepresented in STEM and in making, and research indicates they are more likely to experience negative outcomes when they experience failure.
The intellectual merit of this project centers on establishing a baseline understanding of how failure in making is triggered and experienced by youth, what role educators play in the process, and what can be done to increase persistence and learning, rather than failure being an end-state. The research team will investigate these issues through the use of qualitative and quantitative research methods. In particular, the team will design and evaluate the effectiveness of interventions on increasing the abilities of youth and educators in noticing and responding to failures and increasing positive (e.g., resilience) outcomes. Research sites are selected because they will allow collection of data on youth from a wide range of backgrounds. The research team will also work to test and revise their hypothesized model of the influence of factors on persistence through failures in making. This project is a part of NSF's Maker Dear Colleague Letter (DCL) portfolio (NSF 15-086), a collaborative investment of Directorates for Computer & Information Science & Engineering (CISE), Education and Human Resources (EHR) and Engineering (ENG).
This Research in Service to Practice project, a collaboration of Pepperdine University and the New York Hall of Science, will establish a network of STEM-related Media Making Clubs comprised of after-school students aged 12 - 19 and teachers in the U.S. and in three other countries: Kenya, Namibia and Finland. The media produced by the students may include a range of formats such as videos, short subject films, games, computer programs and specialized applications like interactive books. The content of the media produced by the students will focus on the illustration and teaching of STEM topics, where the shared media is intended to help other students become enthused about and learn the science. This proposal builds on the principal investigator's previous work on localized media clubs by now creating an international network in which after-school students and teachers will collaborate at a distance with other clubs. The central research questions for the project pertain to three themes at the intersection of learning, culture and collaboration: the impact of participatory teaching, virtual networks, and intercultural, global competence. The research will combine qualitative, cross-cultural and big data methods. Critical to the innovation of the project, the research team will also develop a network assessment tool, adapting epistemic network analysis methods to the needs of this initiative. This work is funded 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:
Eric HamiltonKatherine McMillanPriya Mohabir