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
This project investigates long-term human-robot interaction outside of controlled laboratory settings to better understand how the introduction of robots and the development of socially-aware behaviors work to transform the spaces of everyday life, including how spaces are planned and managed, used, and experienced. Focusing on tour-guiding robots in two museums, the research will produce nuanced insights into the challenges and opportunities that arise as social robots are integrated into new spaces to better inform future design, planning, and decision-making. It brings together researchers from human geography, robotics, and art to think beyond disciplinary boundaries about the possible futures of human-robot co-existence, sociality, and collaboration. Broader impacts of the project will include increased accessibility and engagement at two partner museums, interdisciplinary research opportunities for both undergraduate and graduate students, a short video series about the current state of robotic technology to be offered as a free educational resource, and public art exhibitions reflecting on human-robot interactions. This project will be of interest to scholars of Science and Technology Studies, Human Robotics Interaction (HRI), and human geography as well as museum administrators, educators and the general public.
This interdisciplinary project brings together Science and Technology Studies, Human Robotics Interaction (HRI), and human geography to explore the production of social space through emerging forms of HRI. The project broadly asks: How does the deployment of social robots influence the production of social space—including the functions, meanings, practices, and experiences of particular spaces? The project is based on long-term ethnographic observation of the development and deployment of tour-guiding robots in an art museum and an earth science museum. A social roboticist will develop a socially-aware navigation system to add nuance to the robots’ socio-spatial behavior. A digital artist will produce digital representations of the interactions that take place in the museum, using the robot’s own sensor data and other forms of motion capture. A human geographer will conduct interviews with museum visitors and staff as well as ethnographic observation of the tour-guiding robots and of the roboticists as they develop the navigation system. They will produce an ethnographic analysis of the robots’ roles in the organization of the museums, everyday practices of museum staff and visitors, and the differential experiences of the museum space. The intellectual merits of the project consist of contributions at the intersections of STS, robotics, and human geography examining the value of ethnographic research for HRI, the development of socially-aware navigation systems, the value of a socio-spatial analytic for understanding emerging forms of robotics, and the role of robots within evolving digital geographies.
This project is jointly funded by the Science and Technology Studies program in SBE and Advancing Informal STEM Learning (AISL) Program in EHR.
Maker Education scholarship is accumulating increasingly complex understandings of the kinds of learning associated with maker practices along with principles and pedagogies that support such learning. However, even as large investments are being made to spread maker education, there is little understanding of how organizations that are intended targets of such investments learn to develop new maker related educational programs. Using the framework of Expansive Learning, focusing on organizational learning processes resulting in new and unfolding forms of activity, this paper begins to fill
Sense-making with data through the process of visualization—recognizing and constructing meaning with these data—has been of interest to learning researchers for many years. Results of a variety of data visualization projects in museums and science centers suggest that visitors have a rudimentary understanding of and ability to interpret the data that appear in even simple data visualizations. This project supports the need for data visualization experiences to be appealing, accommodate short and long-term exploration, and address a range of visitors’ prior knowledge. Front-end evaluation
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 a two-day conference, along with pre- and post-conference activities, with the goal of furthering the informal science learning field's review of the research and development that has been conducted on data visualizations that have been used to help the public better understand and become more engaged in science. The project will address an urgent need in informal science education, providing a critical first step towards a synthesis of research and technology development in visualization and, thus, to inform and accelerate work in the field in this significant and rapidly changing domain.
The project will start with a Delphi study by the project evaluator prior to the conference to provide an Emerging Field Assessment on data visualization work to date. Then, a two-day conference at the Exploratorium in San Francisco and related activities will bring together AISL-funded PIs, computer scientists, cognitive scientists, designers, and technology developers to (a) synthesize work to date, (b) bring in relevant research from fields outside of informal learning, and (c) identify remaining knowledge gaps for further research and development. The project team will also develop a website with videos of all presentations, conference documentation, resources, and links to social media communities; and a post-conference publication mapping the state of the field, key findings, and promising technologies.
The initiative also has a goal to broaden participation, as the attendees will include a diverse cadre of professionals in the field who contribute to data visualization work.
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.
It is a well-documented fact that women and minorities are currently underrepresented in STEM higher education degree programs and careers. As an outreach measure to these populations, we established the Hexacago Health Academy (HHA), an ongoing summer program. Structured as an informal learning environment with a strong youth initiated mentoring component, HHA uses game-based learning as both a means of health education and stimulating interest in careers in medicine among adolescents from underrepresented minority populations. In this article, we describe the 2015 session of the Hexacago
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TEAM MEMBERS:
Megan MacklinPatrick JagodaIan B. JonesMelissa Gilliam
As the maker movement is increasingly adopted into K-12 schools, students are developing new competences in exploration and fabrication technologies. This study assesses learning with these technologies in K-12 makerspaces and FabLabs.
Our study describes the iterative process of developing an assessment instrument for this new technological literacy, the Exploration and Fabrication Technologies Instrument, and presents findings from implementations at five schools in three countries. Our index is generalizable and psychometrically sound, and permits comparison between student confidence
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TEAM MEMBERS:
Paulo BliksteinZaza KabayadondoAndrew P. MartinDeborah A. Fields
This project, an NSF INCLUDES Design and Development Launch Pilot, managed by the University of Nevada, Reno, addresses the grand challenge of increasing underrepresentation regionally in the advanced manufacturing sector. Using the state's Learn and Earn Program Advanced Career Pathway (LEAP) as the foundation, science, technology, engineering and mathematics (STEM) activities will support and prepare Hispanic students for the region's workforce in advanced manufacturing which includes partnerships with Truckee Meadows Community College (TMCC), the state's Governor's Office of Economic Development, Charles River Laboratories, Nevada Established Program to Stimulate Competitive Research (Nevada EPSCoR) and the K-12 community.
The expected outcomes from the project will inform the feasibility, expandability and transferability of the LEAP framework in diversifying the state's workforce locally and the STEM workforce nationally. Formative and summative evaluation will be conducted with a well-matched comparison group. Dissemination of project results will be disseminated through the Association for Public Land-Grant Universities (APLU), STEM conferences and scholarly journals.
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TEAM MEMBERS:
David ShintaniJulie EllsworthKarsten HeiseRobert StachlewitzRegina Tempel
The University of Texas at Austin's Texas Advanced Computing Center, Chaminade University of Honolulu (CUH), and the Georgia Institute of Technology will lead this NSF INCLUDES Design and Development Launch Pilot (DDLP) to establish a model for data science preparation of Native Hawaiian and Pacific Islander (NHPI) students at the high school and undergraduate levels. The project is premised on the promise of NHPI communities gaining access to, and the ability to work with, large data sets to tackle emerging problems in the Pacific. Such agency over "big data" sets that are relevant to Pacific issues, and contemporary skills in data science, analytics and visualization have the potential to be transformative for community improvement efforts. The effort has the potential to advance knowledge, instructional pedagogy and practices to improve NHPI high school and undergraduate students performance in and attraction to STEM education and careers.
The project team will work to: 1) Increase interest and proficiency in data science and visualization among NHPI high school and undergraduate students through a summer immersion experience that bridges computation and culture; 2) Build data science capacity at an NHPI serving undergraduate institution (CUH) through creation of a certificate program; and 3) Develop and expand partnerships with other organizations with related goals working with NHPI populations. The month-long summer training for 20 NHPI college students, and five NHPI high school students, takes place at CUH and focuses on data science, visualization, and virtual reality, including working on problem sets that require data science approaches and incorporate geographically, socially- and culturally-relevant research themes.
The University of New Hampshire (UNH) NSF INCLUDES Design and Development Launch Pilot project is a collaborative effort with the Community College System of New Hampshire, Advanced Manufacturing (AM) businesses, NH Economic Development, and the University of New Hampshire to address workforce development in the Advanced Manufacturing sector in the state. The Advanced Manufacturing Program (AMP) uses a framework built on the Collective Impact collaboration model that enables AMP partners to innovate, plan, and implement strategies that significantly increase NH's community colleges (CC) as a source for future workers and leaders in AM.
Specifically, this proposal addresses the pressing need for increasing numbers of AM workers through strategies designed to increase the retention of low socioeconomic status (LSES) students in CC STEM degree programs. AMP coordinates four key implementation strategies: 1) Co-requisite remediation within mathematics and quantitative reasoning; 2) Guided Pathways mentorship with "high touch" advising and student guidance resources that combines clearly defined academic pathways leading to 4-year college transfer and job placement; 3) paid work-based learning (WBL) experiences in industry and academic research; and 4) mentor inclusiveness training to prepare the workplace and academic settings to receive LSES students into a supportive climate. Successfully coordinating these four components through the process of Collective Impact collaboration will lead to a flexible and integrated AM workforce pipeline that serves CC AM students, AM industry partners, and the state as a whole. Findings will be disseminated to academic, business, and government stakeholders in NH, the region, and nationally to inform and improve broadening participation initiatives.
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TEAM MEMBERS:
Palligarnai VasudevanStephen HaleBrad KinseyLeslie BarberMelissa Aikens