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
resourceevaluationMuseum and Science Center Exhibits
The linked repository contains select resources from the SICIIT NSF project (Supporting Science and Engineering Identity Change in Immersive Interactive Technologies). The project did not reach its main objective, mainly due to disruptions caused by COVID, but we hope that the materials will be a useful resource for follow-up research.
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TEAM MEMBERS:
Stefan RankAyana AllenGlen MuschioAroutis FosterKapil Dandekar
resourceprojectProfessional Development, Conferences, and Networks
The New York Hall of Science (NYSCI) will convene a two-day participatory design conference of to identify research and education opportunities in informal settings for supporting literacy concerning Artificial Intelligence (AI), especially for diverse and underserved youth whose communities are impacted by the bias in some AI processes. AI uses computer systems that simulate human intelligence. AI systems impact nearly every aspect of daily living, performing tasks underlying navigation apps, facial recognition, e-payments, and social media. AI can perpetuate inequities and biased outcomes in the culture at large. The conference will explore how to promote engagement and conceptual learning among youth about how AI works and what skills are needed to critically use and apply AI. The conference will also explore ways to support the interests of diverse and underserved children and youth in shaping AI and joining the growing STEM workforce that will use AI in their professions.
The conference will identify key features and needs with respect to AI literacy and explore the specific roles that informal learning can play in advancing AI literacy for youth in diverse and underserved communities. Participants in the conference will include designers, learning scientists, researchers, informal and formal educators, and science center professionals. Attendees will work in separate teams and as a group to explore and critique existing AI tools and learning frameworks, discuss lessons learned from promising AI literacy programs, and identify design principles and future directions for research. Specific attention will be paid to informal mechanisms of engagement, promising networks, and research-practice partnerships that take advantage of the unique affordances of informal learning and community services to accelerate AI literacy for historically excluded youth. The insights gained from this work will result in a set of research and programmatic priorities for informal institutions to promote AI literacy in culturally responsive ways. The resulting published guide and community events will broadly disseminate priorities and design principles generated by this convening to help informal learning institutions and community learning organizations identify both assets and priorities for addressing diversity, equity, access, and inclusion issues related to AI literacy.
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.
The AI behind Virtual Humans Exhibit aims to communicate to the public about the capabilities and impact of artificial intelligence (AI) through AI technologies used in Virtual Humans including facial recognition and natural language processing. AI has and will continue to profoundly impact society in the United States and around the globe. It is important to prepare the nation’s youth and the future workforce with fundamental knowledge of AI. Informal settings, such as museums, offer open and flexible opportunities in helping youth and the general public learn about AI. Virtual Humans provide an ideal vehicle to illustrate many fields of AI, as AI is arguably the science of building intelligence that thinks and acts like humans. Led by a multidisciplinary team of researchers with expertise in AI, learning design, and assessment from the Institute for Creative Technologies at University of Southern California and the Lawrence Hall of Science at University of California, Berkeley, this project will develop a Virtual Human exhibit to engage visitors through structured conversations with a Virtual Human, while showcasing how AI drives the Virtual Human’s behavior behind the scenes. The exhibit will include collaborative learning experiences for visitors such as parent-child, siblings and peers to explore what AI is and is not, what AI is and is not capable of, and what impact it will have on their lives.
The project will investigate three research questions: (1) How can a museum exhibit be designed to engage visitor dyads in collaborative learning about AI? (2) How can complex AI concepts underlying the Virtual Human be communicated in a way that is understandable by the general public? And (3) How does and to what extent the Virtual Human exhibit increase knowledge and reduce misconceptions about AI?
The project leverages existing conversational Virtual Human technology developed through decades of collaborative research in AI, including machine vision, natural language processing, automated reasoning, character animation, and machine learning. Set in the informal setting of a museum, the exhibit will be designed following evidence-based research in Computer Supported Collaborative Learning. The project team will use a mixed methods design, drawing on design-based research methodologies and experimental studies. The research team will conduct analysis of visitor observations and interviews for iterative formative improvement. Randomized experimental studies will be conducted in both lab and naturalistic environments to gauge visitor knowledge about AI. Quasi-experimental analyses will be performed to study the relationship between engagement with exhibit features and AI knowledge. The project will produce an interactive exhibit with a Virtual Human installed at the Lawrence Hall of Science and other participating museums, and instruments to measure AI learning. The project will also produce a website where visitors can experience parts of the exhibit online and continue more in-depth learning about AI and the Virtual Human technology. The project holds the potential for producing theoretical and practical advances in helping the general public develop an understanding of AI capability and ethics, advancing knowledge in the process through which young learners develop knowledge about AI, and formulating design principles for creating collaborative learning experiences in informal settings. The results will be disseminated through conference presentations, scholarly publications, and social media. The Virtual Human exhibit will be designed for dissemination and made available for installations at informal science education communities.
The Council for Opportunity in Education, in collaboration with TERC, seeks to advance the understanding of social and cultural factors that increase retention of women of color in computing; and implement and evaluate a mentoring and networking intervention for undergraduate women of color based on the project's research findings. Computing is unique because it ranks as one of the STEM fields that are least populated by women of color, and because while representation of women of color is increasing in nearly every other STEM field, it is currently decreasing in computing - even as national job prospects in technology fields increase. The project staff will conduct an extensive study of programs that have successfully served women of color in the computing fields and will conduct formal interviews with 15 professional women of color who have thrived in computing to learn about their educational strategies. Based on those findings, the project staff will develop and assess a small-scale intervention that will be modeled on the practices of mentoring and networking which have been established as effective among women of color who are students of STEM disciplines. By partnering with Broadening Participation in Computing Alliances and local and national organizations dedicated to diversifying computing, project staff will identify both women of color undergraduates to participate in the intervention and professionals who can serve as mentors to the undergraduates in the intervention phase of the project. Assisting the researchers will be a distinguished Advisory Board that provides expertise in broadening the representation of women of color in STEM education. The external evaluator will provide formative and summative assessments of the project's case study data and narratives data using methods of study analysis and narrative inquiry and will lead the formative and summative evaluation of the intervention using a mixed methods approach. The intervention evaluation will focus on three variables: 1) students' attitudes toward computer science, 2) their persistence in computer science and 3) their participant attitudes toward, and experiences in, the intervention.
This project extends the PIs' previous NSF-funded work on factors that impact the success of women of color in STEM. The project will contribute an improved understanding of the complex challenges that women of color encounter in computing. It will also illuminate individual and programmatic strategies that enable them to participate more fully and in greater numbers. The ultimate broader impact of the project should be a proven, scalable model for reversing the downward trend in the rates at which women of color earn bachelor's degrees in computer science.
Computing fields are foundational to most STEM disciplines and the only STEM discipline to show a consistent decline in women's representation since 1990, making it an important field for STEM educators to study. The explanation for the underrepresentation of women and girls in computing is twofold: a sense that they do not fit within the stereotypes associated with computing and a lack of access to computer games and technologies beginning at an early age (Richard, 2016).
Informal coding education programs are uniquely situated to counter these hurdles because they can offer additional
Increasingly, scientists and their institutions are engaging with lay audiences via media. The emergence of social media has allowed scientists to engage with publics in novel ways. Social networking sites have fundamentally changed the modern media environment and, subsequently, media consumption habits. When asked where they primarily go to learn more about scientific issues, more than half of Americans point to the Internet. These online spaces offer many opportunities for scientists to play active roles in communicating and engaging directly with various publics. Additionally, the proposed research activities were inspired by a recent report by the National Academies of Sciences, Engineering, and Medicine that included a challenge to science communication researchers to determine better approaches for communicating science through social media platforms. Humor has been recommended as a method that scientists could use in communicating with publics; however, there is little empirical evidence that its use is effective. The researchers will explore the effectiveness of using humor for communicating about artificial intelligence, climate science and microbiomes.
The research questions are: How do lay audiences respond to messages about scientific issues on social media that use humor? What are scientists' views toward using humor in constructing social media messages? Can collaborations between science communication scholars and practitioners facilitate more effective practices? The research is grounded in the theory of planned behavior and framing as a theory of media effects. A public survey will collect and analyze data on Twitter messages with and without humor, the number of likes and re-tweets of each message, and their scientific content. Survey participants will be randomly assigned to one of twenty-four experimental conditions. The survey sample, matching recent U.S. Census Bureau data, will be obtained from opt-in panels provided by Qualtrics, an online market research company. The second component of the research will quantify the attitudes of scientists toward using humor to communicate with publics on social media. Data will be collected from a random sample of scientists and graduate students at R1 universities nationwide. Data will be analyzed using descriptive statistics and regression modeling.
The broader impacts of this project are twofold: findings from the research will be shared with science communication scholars and trainers advancing knowledge and practice; and an infographic (visual representation of findings) will be distributed to practitioners who participate in research-practice partnerships. It will provide a set of easily-referenced, evidence-based guidelines about the types of humor to which audiences respond positively on social media.
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:
Sara YeoLeona Yi-Fan SuMichael Cacciatore
resourceprojectProfessional Development, Conferences, and Networks
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.
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
resourceprojectProfessional Development, Conferences, and Networks
The goal of FLIP (Diversifying Future Leadership in the Professoriate), an NSF INCLUDES Design and Development Launch Pilot, is to address the broadening participation challenge of increasing the diversity of the future leadership in the professoriate in computing at research universities as a way to achieve diversity across the field. According to the 2016 CRA Taulbee Survey, only 4.3% of the tenure-track faculty at PhD-granting universities are from underrepresented minorities. This challenge is important to address because diverse faculty contributes to academia in the following critical ways: serve as excellent role models for a diverse study body, bring diverse backgrounds to the student programs and policies developed by the department, and bring diverse perspectives to the research projects and programs. Further, the focus is on research universities, because in practice, key national leadership roles, such as serving on national committees that impact thefield of computing, often come from research universities.
The shared purpose and broad vision of the FLIP launch pilot is to increase faculty diversity in computing at research universities by increasing the diversity of PhD graduates from the top producers of computing faculty. The focus is on four underrepresented groups in computing: African Americans; Hispanics; Native Americans and indigenous peoples; and Persons with Disabilities. The long-term goal is to pursue this vision through strategic partnerships with those institutions that are the top producers of computing faculty and organizations that focus on diverse students in STEM, as well as partnerships that collectively adopt proven strategies for recruiting, graduating, and preparing a diverse set of doctoral students for academic careers. The purpose of the pilot is to establish a unified approach across the different partners that will build upon proven strategies to develop novel practices for increasing the diversity of the PhD graduates from key institutions, thereby increasing the faculty diversity in computing at research universities. For the pilot, FLIP will focus on recruitment and admissions and professional development for current PhD students.
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TEAM MEMBERS:
Valerie TaylorCharles IsbellJeffrey ForbesUniversity of Chicago