In this paper we investigate how people become engaged with open data, what their motivations are, and the barriers and facilitators program participants perceive with regard to using open data effectively.
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TEAM MEMBERS:
Jack ShanleyCamillia MatukOded NovGraham Dove
Cities are facing new demands as their urban populations rapidly grow. Smart City initiatives are being developed to address issues of mobility, infrastructure, security, and safety, while enhancing the quality of life of citizens. One-size-fits-all solutions are not viable. Instead, the diversity of a city's residents, including life experiences, cultural backgrounds, needs, and behaviors, must be taken into account to achieve transformative, citizen-centered solutions. Engineers, scientists, policy makers, entrepreneurs, and thought leaders must be prepared to tackle future Smart City challenges, and address knowledge barriers in understanding the needs of citizens across age, occupation, financial standing, disability, and technology savviness. This National Science Foundation Research Traineeship (NRT) award to the Arizona State University addresses this need by training the next generation of MS and PhD students for careers in Smart Cities-related fields. The project anticipates training thirty-eight (38) MS and PhD students, including twenty-four (24) funded trainees, from the following degree programs: Human and Social Dimensions of Science and Technology; Public Affairs; Computer Science; Civil, Environmental, and Sustainable Engineering; Mechanical & Aerospace Engineering; and Applied Engineering Programs. In addition to trainees, it is envisioned that over 300 other MS and PhD students in STEM disciplines will participate in opportunities made available through this traineeship. The knowledge and technologies developed from this project will contribute toward improving the quality of life for all of society through interdisciplinary, citizen-centered Smart City solutions.
An integrated education-research-practice model focused on the technological, societal, and environmental research aspects of citizen-centered solutions for Smart Cities will be employed to instill trainees with transdisciplinary skills and knowledge through cross-disciplinary courses; experience with leading collaborative, use-inspired research projects; applied learning through internships with partners and teaching opportunities; research experiences through service learning and leadership; and entrepreneurial education. Trainees will pursue research thrusts in Citizen-Centered Design; Smart City Infrastructure and Dynamics; and Socio-Environmental Practices and Policies. These thrusts are embedded in integrative priority application areas of Transportation and Accessibility; Safety, Security, and Risk Reduction; and Engagement and Education. Research efforts will significantly advance data-enabled citizen engagement; urban informatics; Internet-of-Things technologies; inclusion and accessibility; urban infrastructure; transportation systems; cybersecurity; swarm robotics; urban sustainability; quality of life and equity for citizens; hazards management and risk reduction; and societal concerns and ethics of emerging Smart City technologies. Focused efforts will be made to recruit underrepresented minorities, women, and individuals with disabilities, in order to tap underutilized talent, equip them to address the needs of their communities, and increase involvement of these groups in Smart Cities-related fields.
The NSF Research Traineeship (NRT) Program is designed to encourage the development and implementation of bold, new potentially transformative models for STEM graduate education training. The program is dedicated to effective training of STEM graduate students in high priority interdisciplinary research areas through comprehensive traineeship models that are innovative, evidence-based, and aligned with changing workforce and research needs.
This project is funded by the National Science Foundation's (NSF's) Advancing Informal STEM Learning (AISL) program, which supports innovative research, approaches, and resources for use in a variety of learning settings.
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TEAM MEMBERS:
Michael KennedyRam PendyalaCynthia SelinAnn McKennaTroy McDanielGail-Joon AhnSethuraman Panchanathan
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.
Michigan Technological University will collaborate with David Heil and Associates to implement the Family Engineering Program, working in conjunction with student chapters of engineering societies such as the American Society for Engineering Education (ASEE), the Society of Hispanic Professionals (SHP) and a host of youth and community organizations. The Family Engineering Program is designed to increase technological literacy by introducing children ages 5-12 and their parents/caregivers to the field of engineering using the principles of design. The project will reach socio-economically diverse audiences in the upper peninsula of Michigan including Native American, Hispanic, Asian, and African American families. The secondary audience includes university STEM majors, informal science educators, and STEM professionals that are trained to deliver the program to families. A well-researched five step engineering design process utilized in the school-based Engineering is Elementary curriculum will be incorporated into mini design challenges and activities based in a variety of fields such as agricultural, chemical, environmental, and biomedical engineering. Deliverables include the Family Engineering event model, Family Engineering Activity Guide, Family Engineering Nights, project website, and facilitator training workshops. The activity guide will be pilot tested, field tested, and disseminated for use in urban, suburban, and rural settings. Strategic impact will result from the development of content-rich engineering activities for families and the dissemination of a project model that incorporates the expertise of engineering and educational professionals at multiple levels of implementation. It is anticipated that 300 facilitators and 7,000-10,000 parents and children will be directly impacted by this effort, while facilitator training may result in more than 27,000 program participants.
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TEAM MEMBERS:
Neil HutzlerEric IversenChristine CunninghamJoan ChaddeDavid Heil