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
Digital Observation Technology Skills (DOTS) is a framework for integrating modern, mobile technology into outdoor, experiential science education. DOTS addresses longstanding tensions between modern technology and classical outdoor education by carefully selecting appropriate digital technology for educational purposes and by situating these tools in classical experiential pedagogy.
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TEAM MEMBERS:
R. Justin HoughamMarc NutterCaitlin Graham
This study explored the effect of depth of learning (as measured in hours) on creativity, curiosity, persistence and self-efficacy. We engaged ~900 parents and 900 students across 21 sites in Washington, Chicago, Los Angeles, New York, Alabama, Virginia and the United Arab Emirates, in 5-week (10-hr) Curiosity Machine programs. Iridescent trained partners to implement the programs. Thus, this analysis was also trying to establish a baseline to measure any loss in impact from scaling our programs and moving to a “train-the-trainer” model. We analyzed 769 surveys out of which 126 were paired. On
The Sustainability Teams Empower and Amplify Membership in STEM (S-TEAMS), an NSF INCLUDES Design and Development Launch Pilot project, will tackle the problem of persistent underrepresentation by low-income, minority, and women students in STEM disciplines and careers through transdisciplinary teamwork. As science is increasingly done in teams, collaborations bring diversity to research. Diverse interactions can support critical thinking, problem-solving, and is a priority among STEM disciplines. By exploring a set of individual contributors that can be effect change through collective impact, this project will explore alternative approaches to broadly enhance diversity in STEM, such as sense of community and perceived program benefit. The S-TEAMS project relies on the use of sustainability as the organizing frame for the deployment of learning communities (teams) that engage deeply with active learning. Studies on the issue of underrepresentation often cite a feeling of isolation and lack of academically supportive networks with other students like themselves as major reasons for a disinclination to pursue education and careers in STEM, even as the numbers of underrepresented groups are increasing in colleges and universities across the country. The growth of sustainability science provides an excellent opportunity to include students from underrepresented groups in supportive teams working together on problems that require expertise in multiple disciplines. Participating students will develop professional skills and strengthen STEM- and sustainability-specific skills through real-world experience in problem solving and team science. Ultimately this project is expected to help increase the number of qualified professionals in the field of sustainability and the number of minorities in the STEM professions.
While there is certainly a clear need to improve engagement and retention of underrepresented groups across the entire spectrum of STEM education - from K-12 through graduate education, and on through career choices - the explicit focus here is on the undergraduate piece of this critical issue. This approach to teamwork makes STEM socialization integral to the active learning process. Five-member transdisciplinary teams, from disciplines such as biology, chemistry, computer and information sciences, geography, geology, mathematics, physics, and sustainability science, will work together for ten weeks in summer 2018 on real-world projects with corporations, government organizations, and nongovernment organizations. Sustainability teams with low participation by underrepresented groups will be compared to those with high representation to gather insights regarding individual and collective engagement, productivity, and ongoing interest in STEM. Such insights will be used to scale up the effort through partnership with New Jersey Higher Education Partnership for Sustainability (NJHEPS).
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TEAM MEMBERS:
Amy TuiningaAshwani VasishthPankaj Lai
As the world is increasingly dependent upon computing and computational processes associated with data analysis, it is essential to gain a better understanding of the visualization technologies that are used to make meaning of massive scientific data. It is also essential that the infrastructure, the very means by which technologies are developed for improving the public's engagement in science itself, be better understood. Thus, this AISL Innovations in Development project will address the critical need for the public to learn how to interpret and understand highly complex and visualized scientific data. The project will design, develop and study a new technology platform, xMacroscope, as a learning tool that will allow visitors at the Science Museum of Minnesota and the Center of Science and Industry, to create, view, understand, and interact with different data sets using diverse visualization types. The xMacroscope will support rapid research prototyping of public experiences at selected exhibits, such as collecting data on a runner's speed and height and the visualized representation of such data. The xMacroscope will provide research opportunities for exhibit designers, education researchers, and learning scientists to study diverse audiences at science centers in order to understand how learning about data through the xMacroscope tool may inform definitions of data literacy. The research will advance the state of the art in visualization technology, which will have broad implications for teaching and learning of scientific data in both informal and formal learning environments. The project will lead to better understanding by science centers on how to present data to the public more effectively through visualizations that are based upon massive amounts of data. Technology results and research findings will be disseminated broadly through professional publications and presentations at science, education, and technology conferences. The 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. The project is driven by the assumption that in the digital information age, being able to create and interpret data visualizations is an important literacy for the public. The research will seek to define, measure, and advance data visualization literacy. The project will engage the public in using the xMacrocope at the Science Museum of Minnesota and at the Center of Science and Industry's (COSI) science museum and research center in Columbus, Ohio. In both museum settings the public will interact with different datasets and diverse types of visualizations. Using the xMacroscope platform, personal attributes and capabilities will be measured and personalized data visualizations will be constructed. Existing theories of learning (constructivist and constructionist) will be extended to capture the learning and use of data visualization literacy. In addition, the project team will conduct a meta-review related to different types of literacy and will produce a definition with performance measures to assess data visualization literacy - currently broadly defined in the project as the ability to read, understand, and create data visualizations. The research has potential for significant impact in the field of science and technology education and education research on visual learning. It will further our understanding of the nature of data visualization literacy learning and define opportunities for visualizing data in ways that are both personally and culturally meaningful. The project expects to advance the understanding of the role of personalization in the learning process using iterative design-based research methodologies to advance both theory and practice in informal learning settings. An iterative design process will be applied for addressing the research questions by correlating visualizations to individual actions and contributions, exploring meaning-making studies of visualization construction, and testing the xMacroscope under various conditions of crowdedness and busyness in a museum context. The evaluation plan is based upon a logic model and the evaluation will iteratively inform the direction, process, and productivity of the project.
The Lemelson Center for the Study of Invention and Innovation and the National Museum of American History (NMAH) contracted Randi Korn & Associates, Inc. (RK&A) to conduct a summative evaluation of Places of Invention (POI), an exhibition funded by the National Science Foundation. The evaluation was designed to determine the extent to which the exhibition achieved its outcomes: 1)Visitors identify the 21st century skills that inventors practice; 2)Visitors identify characteristics that support innovative communities; 3)Visitors express interest in learning about inventions and/or inventors; 4