Measuring Convergence in Science and Engineering Proceedings of a Workshop (2021) / Chapter Skim
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1 Introduction
1 Introduction
Pages 1-6
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While various definitions exist, the NSF website describes convergence research as having two primary characteristics: It is driven by a specific and compelling problem, and it requires deep integration across disciplines. The convergence paradigm "intentionally brings together intellectually diverse researchers to develop effective ways of communicating across disciplines by adopting common frameworks and a new scientific language.
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WORKSHOP FOCUS The purpose of the workshop was to help NSF and NCSES "set an agenda to inform its methodological research and improve its data collection programs to better measure and assess the implications of convergence for the S&E workforce and enterprise." Entwisle explained how convergence has expanded beyond the term coined nearly 10 years ago when MIT professors Phil Sharp and Robert Langer published their work on convergence and biomedical science in 2011.2 Initially, convergence focused on joining engineering, physical science, and life science within academic institutions. It now has expanded to encompass novel disciplines with new outcomes.
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The COVID-19 pandemic has impacted lives everywhere, for example, in terms of health, education, business, and social supports. As one way of improving the quality of life in these circumstances, Lupia called attention to NSF's Convergence Accelerator Program, which accelerates use-inspired convergence research in areas of national importance.3 Quoting American chemist Linus Pauling, he proposed "the best way to have good ideas is to have a lot of ideas." Lupia added that the types of good ideas that can have the largest social impact are almost always novel combinations of existing concepts.
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NSF's Social, Behavioral and Economic Sciences Directorate (SBE) seeks to support "rigorous, precise research that empowers people and improves quality of life." SBE does this by supporting groundbreaking research, the creation of fundamental data and analytic infrastructure, and essential training.
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WORKSHOP GOALS FOR THE NATIONAL CENTER FOR SCIENCE AND ENGINEERING STATISTICS Emilda Rivers (director, NCSES) described the needs, goals, and challenges for NCSES relative to the measurement of convergence.
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The final sessions of the workshop focused on questions related to the feasibility of collecting national-level data on convergence, implementation considerations, and discussions among workshop participants about how NCSES could move the work in this area forward. The full meeting agenda and biographical sketches of steering committee members and workshop presenters appear in the appendixes.
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