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.
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
The data collection procedure and process is one of the most critical components in a research study that affects the findings. Problems in data collection may directly influence the findings, and consequently, may lead to questionable inferences. Despite the challenges in data collection, this study provides insights for STEM education researchers and practitioners on effective data collection, in order to ensure that the data is useful for answering questions posed by research. Our engineering education research study was a part of a three-year, NSF funded project implemented in the Midwest
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TEAM MEMBERS:
Ibrahim YeterAnastasia Marie RynearsonHoda EhsanAnnwesa DasguptaBarbara FagundesMuhsin MeneskeMonica Cardella
Integrating science, technology, engineering, and mathematics (STEM) subjects in pre-college settings is seen as critical in providing opportunities for children to develop knowledge, skills, and interests in these subjects and the associated critical thinking skills. More recently computational thinking (CT) has been called out as an equally important topic to emphasize among pre-college students. The authors of this paper began an integrated STEM+CT project three years ago to explore integrating these subjects through a science center exhibit and a curriculum for 5-8 year old students. We
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TEAM MEMBERS:
Morgan HynesMonica CardellaTamara MooreSean BrophySenay PurzerKristina TankMuhsin MeneskeIbrahim YeterHoda Ehsan
Computational Thinking (CT) is an often overlooked, but important, aspect of engineering thinking. This connection can be seen in Wing’s definition of CT, which includes a combination of mathematical and engineering thinking required to solve problems. While previous studies have shown that children are capable of engaging in multiple CT competencies, research has yet to explore the role that parents play in promoting these competencies in their children. In this study, we are taking a unique approach by investigating the role that a homeschool mother played in her child’s engagement in CT
Given the growth of technology in the 21st century and the growing demands for computer science skills, computational thinking has been increasingly included in K-12 STEM (Science, Technology, Engineering and Mathematics) education. Computational thinking (CT) is relevant to integrated STEM and has many common practices with other STEM disciplines. Previous studies have shown synergies between CT and engineering learning. In addition, many researchers believe that the more children are exposed to CT learning experiences, the stronger their programming abilities will be. As programming is a
For the past two decades, researchers and educators have been interested in integrating engineering into K-12 learning experiences. More recently, computational thinking (CT) has gained increased attention in K-12 engineering education. Computational thinking is broader than programming and coding. Some describe computational thinking as crucial to engineering problem solving and critical to engineering habits of mind like systems thinking. However, few studies have explored how computational thinking is exhibited by children, and CT competencies for children have not been consistently defined
Informal learning environments such as science centers and museums are instrumental in the promotion of science, technology, engineering, and mathematics (STEM) education. These settings provide children with the chance to engage in self-directed activities that can create a of lifelong interest and persistence in STEM. On the other hand, the presence of parents in these settings allows children the opportunity to work together and engage in conversations that can boost understanding and enhance learning of STEM topics. To date, a considerable amount of research has focused on adult-child
Computational Thinking (CT) is a relatively new educational focus and a clear need for learners as a 21st century skill. This proposal tackles this challenging new area for young learners, an area greatly in need of research and learning materials. The Principal Investigators will develop and implement integrated STEM+C museum exhibits and integrate CT in their existing engineering design based PictureSTEM curriculum for K-2 students. They will also pilot assessments of the CT components of the PictureSTEM curriculum. This work will make a unique contribution to the available STEM+C learning materials and assessments. There are few such materials for the kindergarten to second grade (K-2) population they will work with. They will research the effects of the curriculum and the exhibits with a mixed methods approach. First, they will collect observational data and conduct case studies to discover the important elements of an integrated STEM+C experience in both the formal in-school setting with the curriculum and in the informal out-of-school setting with families interacting with the museum exhibits. This work will provide a novel way to understand the important question of how in- and out-of-school experiences contribute to the development of STEM and CT thinking and learning. Finally, they will collect data from all participants to discover the ways that their activities lead to increases in STEM+C knowledge and interest.
The Principal Investigators will build on an integrated STEM curriculum by integrating CT and develop integrated museum exhibits. They base both activities on engineering design implemented through challenge based programming activities. They will research and/or develop assessments of both STEM+C integrated thinking and CT. Their research strategy combines Design Based Research and quantitative assessment of the effectiveness of the materials for learning CT. In the first two years of their study, they will engage in iterations on the design of the curriculum and the exhibits based on observation and case-study data. There will be 16 cases that draw from each grade level and involve data collection for the case student in both schools and museums. They will also use this work to illuminate what integrated STEM+C thinking and learning looks like across formal and informal learning environments. Based in some part on what they discover in this first phase, they will conduct the quantitative assessments with all (or at least most) students participating in the study
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.