Roundtable on Data Science Postsecondary Education: A Compilation of Meeting Highlights

National Academies of Sciences, Engineering, and Medicine

doi:10.17226/25804

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Roundtable on Data Science Postsecondary Education

A Compilation of Meeting Highlights

(2020)

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Established in December 2016, the National Academies of Sciences, Engineering, and Medicine's Roundtable on Data Science Postsecondary Education was charged with identifying the challenges of and highlighting best practices in postsecondary data science education. Convening quarterly for 3 years, representatives from academia, industry, and government gathered with other experts from across the nation to discuss various topics under this charge. The meetings centered on four central themes: foundations of data science; data science across the postsecondary curriculum; data science across society; and ethics and data science. This publication highlights the presentations and discussions of each meeting.

Contributor(s): National Academies of Sciences, Engineering, and Medicine; Division on Engineering and Physical Sciences; Division of Behavioral and Social Sciences and Education; Board on Mathematical Sciences and Analytics; Committee on Applied and Theoretical Statistics; Computer Science and Telecommunications Board; Board on Science Education; Linda Casola, Rapporteur

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Suggested Citation

National Academies of Sciences, Engineering, and Medicine. 2020. Roundtable on Data Science Postsecondary Education: A Compilation of Meeting Highlights. Washington, DC: The National Academies Press. https://doi.org/10.17226/25804.

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Publication Info

223 pages | 6 x 9 |

ISBNs:

Paperback: 978-0-309-67770-7
Ebook: 978-0-309-67773-8

DOI: https://doi.org/10.17226/25804

Chapters		skim
Front Matter	i-xiv
1 Introduction	1-7
2 Meeting #1: The Foundations of Data Science from Statistics, Computer Science, Mathematics, and Engineering	8-16
3 Meeting #2: Examining the Intersection of Domain Expertise and Data Science	17-30
4 Meeting #3: Data Science Education in the Workplace	31-45
5 Meeting #4: Alternative Mechanisms for Data Science Education	46-61
6 Meeting #5: Integrating Ethical and Privacy Concerns into Data Science Education	62-77
7 Meeting #6: Improving Reproducibility by Teaching Data Science as a Scientific Process	78-93
8 Meeting #7: Programs and Approaches for Data Science Education at the Ph.D. Level	94-106
9 Meeting #8: Challenges and Opportunities to Better Engage Women and Minorities in Data Science Education	107-121
10 Meeting #9: Motivating Data Science Education Through Social Good	122-137
11 Meeting #10: Improving Coordination Between Academia and Industry	138-156
12 Meeting #11: Data Science Education at Two-Year Colleges	157-178
References	179-180
Appendixes	181-182
Appendix A: Biographical Sketches of Roundtable Members	183-200
Appendix B: Meeting Participants	201-208

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