This RAPID was submitted in response to the NSF Dear Colleague letter related to the COVID-19 pandemic. This award is made by the AISL program in the Division of Research on Learning, using funds from the Coronavirus Aid, Relief, and Economic Security (CARES) Act. COVID-19 presents a national threat to the health of children and families, presenting serious implications for the mental and physical health of children. Child development scientists have already warned of increasing stress levels among the U.S. child population, especially those in low-income families of color. In addition, Latino children are disproportionately impoverished, and benefit from culturally relevant information. Parents and caregivers need to be armed with effective science-based strategies to improve child prospects during this global crisis. Harnessing well-established partnership (including with local TV news partners and parent-serving organizations) strengthens the potential for broad impacts on the health and well-being of children and families during the COVID-19 pandemic. As the pandemic persists, widely disseminating accurate research-based strategies to support parents and families, with a focus on low-income Latino parents, is crucial to meeting the needs of the nation's most vulnerable during this global crisis. The award addresses this urgent need by producing research-based news videos on child development for distribution on broadcast television stations that reach low income Latino parents. The videos will communicate research-based recommendations regarding COVID-19 in ways that are relatable to Latino parents and lead to positive parenting during this pandemic. A "how to" video will also be produced showing parents how to implement some of the practices. Project partners include Abriendo Puertas, the largest U.S. parenting program serving low-income Latinos, and Ivanhoe Broadcasting.
Research questions include: 1) What information do parents need (and potentially what misinformation they are being exposed to)? 2) What are they sharing? 3) How does this vary geographically? 4) Can researchers detect differences in public engagement in geographic areas where TV stations air news videos as compared to areas that don't? This project will use data and communication science research strategies (e.g. natural language processing from online sites where parents are asking questions and sharing information) to inform the content of the videos and lead to the adoption of featured behaviors. Data from web searches, public Facebook pages, and Twitter posts will be used to gain a window into parents' main questions and concerns including information regarding hygiene, how to talk about the pandemic without frightening their children, or determining veracity of what they hear and see related to the pandemic.
This organic approach can detect concerns that parents may be unlikely to ask doctors or discuss in focus groups. Methodologically, the researchers will accomplish this by natural language analysis of the topics that parents raise; the words and phrases they use to talk about specific content; and any references to external sources of information. Where possible, the researchers will segment this analysis by geography to see if there are geographical differences in information needs and discourse. A research brief will share new knowledge gained with the field on how to respond to national emergencies, such as the COVID-19 pandemic, using local TV news and reinforcement of messages across contexts. The findings from this award will provide a knowledge base that can be utilized to better inform responses to national emergencies in the future. By broadly disseminating these findings through a research brief, the project?s innovative research will advance the field of communication science.
This 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.
This poster provides an overview, program goals, evaluation plan, and research questions for the AISL project, Techbridge Broad Implementation: An Innovative Model to Inspire Girls in STEM Careers. The poster was presented at the 2014 AISL PI Meeting.