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A report summarizing the “Keeping Data Science Broad” series including data science challenges, visions for the future, and community asks. The goal of the Keeping Data Science Broad series was to garner community input into pathways for keeping data science education broadly inclusive across sectors, institutions, and populations. Input was collected from a community input survey, three webinars (Data Science in the Traditional Context, Alternative Avenues for Development of Data Science Education Capacity, and Big Picture for a Big Data Science Education Network available to view through the South Big Data Hub YouTube channel) and an interactive workshop (Negotiating the Digital and Data Divide). Through these venues, we explore the future of data science education and workforce at institutions of higher learning that are primarily teaching-focused. The workshop included representatives from sixty data science programs across the nation, either traditional or alternative, and from a range of institution types including community colleges, Historically Black Colleges and Universities (HBCU’s), Hispanic-Serving Institutions (HSI’s), other minority-led and minority-serving institutions, liberal arts colleges, tribal colleges, universities, and industry partners.
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Systematic shifts in scaling behavior based on organizational strategy in universities
To build better theories of cities, companies, and other social institutions such as universities, requires that we understand the tradeoffs and complementarities that exist between their core functions, and that we understand bounds to their growth. Scaling theory has been a powerful tool for addressing such questions in diverse physical, biological and urban systems, revealing systematic quantitative regularities between size and function. Here we apply scaling theory to the social sciences, taking a synoptic view of an entire class of institutions. The United States higher education system serves as an ideal case study, since it includes over 5,800 institutions with shared broad objectives, but ranges in strategy from vocational training to the production of novel research, contains public, nonprofit and for-profit models, and spans sizes from 10 to roughly 100,000 enrolled students. We show that, like organisms, ecosystems and cities, universities and colleges scale in a surprisingly systematic fashion following simple power-law behavior. Comparing seven commonly accepted sectors of higher education organizations, we find distinct regimes of scaling between a school’s total enrollment and its expenditures, revenues, graduation rates and economic added value. Our results quantify how each sector leverages specific economies of scale to address distinct priorities. Taken together, the scaling of features within a sector along with the shifts in scaling across sectors implies that there are generic mechanisms and constraints shared by all sectors, which lead to tradeoffs between their different societal functions and roles. We highlight the strong complementarity between public and private research universities, and community and state colleges, that all display superlinear returns to scale. In contrast to the scaling of biological systems, our results highlight that much of the observed scaling behavior is modulated by the particular strategies of organizations rather than an immutable set of constraints.
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- PAR ID:
- 10309394
- Editor(s):
- Amaral, Luís A.
- Date Published:
- Journal Name:
- PLOS ONE
- Volume:
- 16
- Issue:
- 10
- ISSN:
- 1932-6203
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1371/journal.pone.0254582
