Data science is ever-present in modern life. The need to learn with and about data science is becoming increasingly important in a world where the quantity of data is constantly growing, where one’s own data are often being harvested and marketed, where data science career opportunities are rapidly increasing, and where understanding statistics, data sources, and data representation is integral to understanding STEM and the world around us. Museums have the opportunity to play a critical role in introducing the public to data science concepts in ways that center personal relevance, social connections and collaborative learning. However, data science and statistics are difficult concepts to distill and provide meaningful engagement with during the brief learning experiences typical to science museums. This Pilot and Feasibility study brings together data scientists, data science educators, and museum exhibit designers to consider these questions:
What are the important data science concepts for the public to explore and understand in museum exhibits?
How can museum exhibits be designed to support visitors with diverse backgrounds and experiences to engage with these data science concepts?
What principles can shape these designs to promote broadening participation in data science specifically and STEM more broadly?
This Pilot and Feasibility project combines multidisciplinary expert convening, feasibility testing, and early exploratory prototyping around the focal topic of data science exhibits. Project partners, TERC, the Museum of Science, Boston, and The Tech Interactive in San Jose will engage in an iterative process to develop a theoretical grounding and practical guidance for museum practitioners. The project will include two convenings, bringing together teams of experts from the fields of data science, data science education and museum exhibit design. Prior to the first convening, an initial literature summary and a survey of convening participants will be conducted, culminating in a preliminary list of big ideas about data science. Periodically, participants will have the opportunity to rank, annotate and expand this list, as a form of ongoing data collection. During the convenings, participants will explore the preliminary list, share related work from the three disciplines, engage with related data science activities in small groups, and work together to build consensus around promising data science topics and approaches for exhibits. Participant evaluation will allow for iterative improvement of the convenings and the capture of missed points or overlooked topics. After each convening, museum partners will create prototypes that respond to the convening conversations. Prototypes will be pilot tested (evaluated) with an intentionally recruited group of families that includes both frequent visitors and those who are less likely to visit the museum; diversity in terms of race, languages and dis/ability will be reflected in selection. Pilot data collection will consist of structured observations and interviews. Results from the first round of prototyping will be shared with convening participants as a way to modify the list of big ideas and to further interrogate the feasibility of communicating these ideas in an exhibit format. Results from the convenings and from both rounds of prototyping will be combined in a guiding document that will be shared on all three partner websites, and more broadly with the informal STEM learning field. The team will also host a workshop for practitioners interested in designing data science exhibits, and present at a conference focused on museum exhibits and their design.
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.
Historic art objects provide a collection of materials that have been naturally aged for decades or even centuries. In addition to the intrinsic archival value of these materials, they are also models for understanding property degradation over long periods of time. This project aims to develop computational and experimental tools needed to understand how these changes take place. To accomplish this task a research network has been established between Northwestern University and leaders in cultural heritage science from the Rijksmuseum and the University of Amsterdam in the Netherlands, the National Research Council in Italy, and the Synchrotron Soleil in France. This new infrastructure promises to deliver a significant enhancement of research and education resources (networks, partnership and increased access to facilities and instrumentation) to a diverse group of users. The art objects central to the project provide a series of well-defined case studies for investigating complex materials systems that are both applicable to materials education and push the limits of the existing analytical tools, thus inspiring instrumental innovations across broad sectors of the physical sciences. Further development of these tools will enable art conservators to more effectively make informed decisions about treatments of works of art, and to understand long-term materials degradation more generally. The project will also deliver a significant enhancement of research and education infrastructure by a diverse group of users and will provide meaningful, international research experience to 50 participants, with a strong emphasis on scientists at the beginning of their careers. In addition, the connections between science and art will illustrate the creative aspects of both disciplines to a very broad audience, attracting a more representative cross section of people into science.
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Kenneth ShullFrancesca CasadioOliver CossairtAggelos KatsaggelosMarc Walton
Becoming computationally literate is increasingly crucial to everyday life and to expanding workforce capacity. Research suggests that computational literacy--knowing what, when, how, and why to use the ideas of computer science, in combination with the capacity to view problems and potential solutions through the lens of computational structures and procedures--can be supported through digital game play. This project aims to develop a social and creative exhibit game that foregrounds aspects of computer science, specifically artificial intelligence (AI) and computer programming, in ways that enable youth to explore, construct, and share computational complex systems content with one another and other museum visitors. To play the game, pairs of youth visitors will use code cards to program the behavior of AI animals in a virtual forest. As they do so, youth will engage with computational literacy practices, such as basic computer programming, describing their computational ideas, and doing computational problem solving with their friends. Their activity will be projected on a large screen as a strategy for enabling youth to test, rehearse, and communicate their computational ideas and to also interest other visitors into computational problem solving.
Using multi-perspective and iterative design-based research, university learning scientists, museum practitioners, and game developers will pursue research questions around how science museums can better engage youth who are traditionally underrepresented in computer science in complex computational practices. Data sources will include interactive-log data, observations of visitor interactions with the game, visitor interviews, and visitor surveys. A multimodal and mixed methods approach that searches for convergences between qualitative analysis, quantitative analysis, and learning analytics will be used to generate research findings. Changes in computational literacy will be assessed by evaluating what problems visitors choose to solve with programming, how they frame those problems, and their selections from among possible solutions, what they program, how they program, and how they describe programming ideas. The results of this project will include: 1) a social, interactive gameplay experience that supports the development of computational literacy; 2) design principles for game-based exhibits that facilitate development of computational literacy; and 3) new knowledge of variations in design and gameplay across diverse gameplay users, including those from underrepresented groups in computer science. It is anticipated that 1,000 museum youth visitors will directly participate in the study.
This project is funded by the Advancing Informal STEM Learning (AISL) program, which 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.
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TEAM MEMBERS:
Matthew BerlandLeilah LyonsMatthew Cannady
This one-year Collaborative Planning project seeks to bring together an interdisciplinary planning team of informal and formal STEM educators, researchers, scientists, community, and policy experts to identify the elements, activities, and community relationships necessary to cultivate and sustain a thriving regional early childhood (ages 3-6) STEM ecosystem. Based in Southeast San Diego, planning and research will focus on understanding the needs and interests of young Latino dual language learners from low income homes, as well as identify regional assets (e.g., museums, afterschool programs, universities, schools) that could coalesce efforts to systematically increase access to developmentally appropriate informal STEM activities and resources, particularly those focused on engineering and computational thinking. This project has the potential to enhance the infrastructure of early STEM education by providing a model for the planning and development of early childhood focused coalitions around the topic of STEM learning and engagement. In addition, identifying how to bridge STEM learning experiences between home, pre-k learning environments, and formal school addresses a longstanding challenge of sustaining STEM skills as young children transition between environments. The planning process will use an iterative mixed-methods approach to develop both qualitative and quantitative and data. Specific planning strategies include the use of group facilitation techniques such as World Café, graphic recording, and live polling. Planning outcomes include: 1) a literature review on STEM ecosystems; 2) an Early Childhood STEM Community Asset Map of southeast San Diego; 3) a set of proposed design principles for identifying and creating early childhood STEM ecosystems in low income communities; and 4) a theory of action that could guide future design and research. This project is funded by the Advancing Informal STEM Learning program, which seeks to advance new approaches to, and evidence-based understanding of, the design and development of STEM learning in informal environments.
The Environmental Scientist-in-Residence Program will leverage NOAA s scientific assets and personnel by combining them with the creativity and educational knowledge of the pioneer hands-on science center. To do this, the program will embed NOAA scientists in a public education laboratory at the Exploratorium. Working closely with youth Explainers, exhibit developers, and Web and interactive media producers at the Exploratorium, NOAA scientists will share instruments, data, and their professional expertise with a variety of public audiences inside the museum and on the Web. At the same time the scientists will gain valuable skills in informal science communication and education. Through cutting-edge iPad displays, screen-based visualizations, data-enriched maps and sensor displays, and innovative interactions with visitors on the museum floor, this learning laboratory will enable NOAA scientists and Exploratorium staff to investigate new hands-on techniques for engaging the public in NOAA s environmental research and monitoring efforts.
Computational social science represents an interdisciplinary approach to the study of reality based on advanced computer tools. From economics to political science, from journalism to sociology, digital approaches and techniques for the analysis and management of large quantities of data have now been adopted in several disciplines. The papers in this JCOM commentary focus on the use of such approaches and techniques in the research on science communication. As the papers point out, the most significant advantages of a computational approach in this sector include the chance to open up a range
This project entails the creation of a coordinated colony of robotic bees, RoboBees. Research topics are split between the body, brain, and colony. Each of these research areas is drawn together by the challenges of recreating various functionalities of natural bees. One such example is pollination: Bees coordinate to interact with complex natural systems by using a diversity of sensors, a hierarchy of task delegation, unique communication, and an effective flapping-wing propulsion system. Pollination and other agricultural tasks will serve as challenge thrusts throughout the life of this project. Such tasks require expertise across a broad spectrum of scientific topics. The research team includes experts in biology, computer science, electrical and mechanical engineering, and materials science, assembled to address fundamental challenges in developing RoboBees. An integral part of this program is the development of a museum exhibit, in partnership with the Museum of Science, Boston, which will explore the life of a bee and the technologies required to create RoboBees.
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TEAM MEMBERS:
Robert WoodRadhika NagpalJ. Gregory MorrisettGu-Yeon WeiJoseph Ayers
In 2013 and 2014, the Museum of Science (MOS) partnered with Dr. Rob Wood’s lab at Harvard University’s School of Engineering and Applied Sciences (SEAS) to create an exhibition about Wood’s Robotic Bees (RoboBees) project. The Microrobotics Takes Flight exhibition (referred to in the original grant as the RoboBees exhibition) consists of three interactive components and an introductory section. The three interactive components are modeled on the three different engineering teams working on the RoboBees project: the Brain, the Body, and the Colony teams. The purpose of the evaluation was
This article describes the software architecture of an autonomous, interactive tour-guide robot. It presents a modular and distributed software architecture, which integrates localization, mapping, collision avoidance, planning, and various modules concerned with user interaction and Web-based telepresence. At its heart, the software approach relies on probabilistic computation, on-line learning, and any-time algorithms. It enables robots to operate safely, reliably, and at high speeds in highly dynamic environments, and does not require any modifications of the environment to aid the robot's
Bridging Earth and Mars (BEAM): Engineering Robots to Explore the Red Planet engages the general public and K-8 students in exhibits and programs designed to foster awareness of robotic technology, computer programming, and the challenges and opportunities inherent in NASA missions and S-STEM careers. The Saint Louis Science Center (SLSC) of St. Louis, Missouri is the lead institution and project site; partners include Washington University in St. Louis, Saint Louis University, the St. Louis regional FIRST Robotics organization, and the Challenger Learning Center-St. Louis. Project goals are to: 1) inform, engage, and inspire the public to appreciate NASA’s Mission by sharing findings and information about NASA’s missions to Mars; 2) ignite interest in S-STEM topics and careers for diverse K-8 students; and, 3) encourage students in grades 6-8 to sustain participation in educational experiences along the S-STEM careers pipeline. The SLSC will design and build a Martian surface and panorama where two rovers can be remotely controlled. Visitors in the McDonnell Planetarium will use controllers to program rover exploration of the Martian landscape in real-time. Visitors in SLSC’s Cyberville gallery, located one-quarter mile away across a highway-spanning enclosed bridge, will program the second rover with simulated time lag and view its movements via a two-way camera system. SLSC will organize and host a series of Innovation Workshops for K-8 students, each featuring teamwork-building engineering challenges from current and updated NASA-based science curricula. Participants will be recruited from SLSC community partners, which include community centers and faith-based programs for underserved families.