The National Academies of Science, Engineering, and Medicine Roundtable on Data Science Postsecondary Education was convened in 2016 to work to develop a coherent vision for the emerging field of data science. The Roundtable, which consists of representatives from industry, government, and academia meets quarterly for a day to discuss best practices, ways to support the growing community, and approaches to help advance data science education.
Full information about the roundtable including narrative summaries of past meetings can be found at https://nas.edu/dsert
We thought that the record of the roundtable would be blog-worthy for a number of reasons. First, each of the prior roundtable meetings have focused on a number of provocative and important topics, with narrative summaries provided (as well as high quality recording of the presentations and discussion). Second, it’s timely, as on Wednesday, June 12th the roundtable will be meeting virtually from noon-5:00pm EDT to discuss “data science education at two-year colleges”. Want to participate live? Free signups are available at https://www.eventbrite.com/e/data-science-education-at-two-year-colleges-registration-60945737341
Past meeting topics include:
- March 29, 2019 Improving Coordination between Academia and Industry
- December 10, 2018: Motivating Data Science Education through Social Good
- September 17, 2018: Challenges and Opportunities to Better Engage Women and Minorities in Data Science Education
- June 13, 2018: Programs and Approaches for Data Science Education at the PhD Level
- March 23, 2018: Improving Reproducibility by Teaching Data Science as a Scientific Process
- December 8, 2017: Integrating Ethical and Privacy Concerns into Data Science Education
- October 20, 2017: Alternative Mechanisms for Data Science Education
- May 1, 2017: Data Science Education in the Workplace
- March 20, 2017: Examining the Intersection of Domain Expertise and Data Science
- December 14, 2016: The Foundations of Data Science from Statistics, Computer Science, Mathematics, and Engineering
Take home
I’ve found each of the roundtable meetings to be rewarding in that they have focused on a particular angle and brought together top experts to share their insights, vision for the future, and areas that require more work. Two examples that stand out for me are the discussions of ethical and privacy concerns (https://sites.nationalacademies.org/DEPS/BMSA/DEPS_178021) and the discussions of diversity and inclusion (see https://sites.nationalacademies.org/DEPS/BMSA/DEPS_187416 and also https://teachdatascience.com/diversity). The roundtables have brought many voices together to share their wisdom. I’d encourage you to download a few of the narrative summaries as well as to sign up and participate in the two year college discussion on June 12th.
Learn more
More About the Roundtable (from the NASEM website)
The Roundtable on Data Science Postsecondary Education brings together representatives from academic data science programs, funding agencies, professional societies, foundations, and industry to discuss the community’s needs, best practices, and ways to move forward. The roundtable will help affected communities develop a coherent and shared view of the emerging field of data science and of how best to prepare large numbers of professionals to help realize the potential of this field.
The roundtable convenes four meetings per year. Each meeting focuses on a topic related to data science education or practice, and consists of presentations from experts followed by open discussions of the roundtable. All meetings are open to the public and advertised to the broader data science community. Meetings will be webcast live with the capability for remote participation, and all videos and slides from each meeting will be posted online. Meeting highlights will be produced following each meeting to summarize the presentations and discussions that occurred.
Roundtable members: http://sites.nationalacademies.org/DEPS/BMSA/DEPS_175782
The roundtable is sponsored by the Gordon and Betty Moore Foundation, the National Institutes of Health, the National Academy of Sciences W. K. Kellogg Foundation Fund, the Association for Computing Machinery, the American Statistical Association, and the Mathematical Association of America.
About this blog
Each day during the summer of 2019 we intend to add a new entry to this blog on a given topic of interest to educators teaching data science and statistics courses. Each entry is intended to provide a short overview of why it is interesting and how it can be applied to teaching. We anticipate that these introductory pieces can be digested daily in 20 or 30 minute chunks that will leave you in a position to decide whether to explore more or integrate the material into your own classes. By following along for the summer, we hope that you will develop a clearer sense for the fast moving landscape of data science. Sign up for emails at https://groups.google.com/forum/#!forum/teach-data-science (you must be logged into Google to sign up).
We always welcome comments on entries and suggestions for new ones.