This project will teach foundational computational thinking (CT) concepts to preschoolers by creating a series of mobile apps to guide families through sequenced sets of videos and hands-on activities. To support families at home it would also develop a new library model to build librarians' computational thinking content knowledge and self-efficacy so they can support parents' efforts with their children. Computational thinking is a an increasingly critical skill for learning and success in the workforce. It includes the ability to identify problems, brainstorm and generate solutions and processes that can be communicated and followed by computers or humans. There are few projects that introduce computational thinking to young children. Very little research has been done on the ways that parents can facilitate children's engagement in CT skills. And developing a model that trains and supports librarians to become virtual coaches of parents as they engage with their children in CT, will leverage and build the expertise of librarians. The project's target audience includes parents and children living in rural areas where access to CT learning may be very limited. Project partners include the EDC, a major research organization, the American Library Association, and BUILD, a national association that promotes collaborations across library, kindergarten readiness, and public media programming.
The formative research study asks: 1) What supports do parents of preschoolers in rural communities need in order to effectively engage in CT with their children at home? and 2) How can libraries in rural communities support joint CT exploration in family homes? The summative research study asks: 3) how can an intervention that combines media resources, mobile technology, and library supports foster sustained joint parent/child engagement and positive attitudes around CT? Researchers will develop a parent survey, adapting several scales from previously developed instruments that ask parents to report on children's use of CT-related vocabulary and CT-related attitudes and dispositions. Survey scales will assess librarians' attitudes towards CT, as well as their self-efficacy in supporting parents in CT in a virtual environment. During the formative study, EDC will pilot-test survey scales with 30 parents and 6 librarians in rural MS and KY. Analyses will be primarily qualitative and will be geared toward producing rapid feedback for the development team. Quantitative analyses will be used on parent app use, using both time query and back-end data, exploring factors associated with time spent using apps. The summative study will evaluate how the new media resources and mobile technology, in combination with the library virtual implementation model, support families' joint engagement with CT, and positive attitudes around CT. The researchers will recruit 125 low-income families with 4- to 5-year-old children in rural MS and KY to participate in the study. They will randomly assign families within each library to the full intervention condition, including media resources, mobile technology, and library support delivered through the virtual implementation model, or the media and mobile-technology-only condition. This design will allow researchers to understand more fully the additional benefit of library support for rural families' sustained engagement, and conversely, see the comparative impact of a media- and mobile-technology only intervention, given that some families might not be able to access virtual or physical library support.
As part of its overall strategy to enhance learning in informal environments, the Advancing Informal STEM Learning (AISL) program seeks to advance new approaches to, and evidence-based understanding of, the design and development of STEM learning in informal environments. This includes providing multiple pathways for broadening access to and engagement in STEM learning experiences, advancing innovative research on and assessment of STEM learning in informal environments, and developing understandings of deeper learning by participants. This project is co-funded by the Innovative Technology Experiences for Students and Teachers (ITEST) program, which supports projects that build understandings of practices, program elements, contexts and processes contributing to increasing students' knowledge and interest in science, technology, engineering, and mathematics (STEM) and information and communication technology (ICT) careers.
This Innovations in Development award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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.
In 2008, the WGBH Educational Foundation, along with the Association of Computing Machinery, was awarded a grant from the National Science Foundation, Directorate for Computer and Information Science and Engineering, under the Broadening Participation in Computing Program (NSF 0753686). The purpose of the grant was to develop a major new initiative to reshape the image of computing among college-bound high school students. Based on its market research results, WGBH developed a website and other resources that were intended for use by teachers, parents and students. Concord Evaluation Group