ERIC Number: ED612154
Record Type: Non-Journal
Publication Date: 2020
Pages: 223
Abstractor: As Provided
ISBN: 978-0-309-67770-7
ISSN: N/A
EISSN: N/A
Available Date: N/A
Roundtable on Data Science Postsecondary Education: A Compilation of Meeting Highlights
Casola, Linda
National Academies Press
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. [Linda Casola served as the Rapporteur for this report. Additional support for this report was received from the Gordon and Betty Moore Foundation.]
Descriptors: Meetings, Data Analysis, Postsecondary Education, Statistics Education, Longitudinal Studies, College Faculty, Industry, Government Employees, Specialists, Curriculum Development, Ethics, Best Practices, Teaching Methods, Barriers, Higher Education, Mathematics, Engineering, Workplace Learning, Privacy, Computer Science Education, Mathematics Education, Engineering Education, Doctoral Programs, Scientific Research, Two Year Colleges, School Business Relationship, Correlation, Social Responsibility
National Academies Press. 500 Fifth Street NW, Washington, DC 20001. Tel: 888-624-8373; Tel: 202-334-2000; Fax: 202-334-2793; e-mail: Customer_Service@nap.edu; Web site: http://www.nap.edu
Publication Type: Reports - Descriptive; Speeches/Meeting Papers
Education Level: Postsecondary Education; Higher Education; Two Year Colleges
Audience: N/A
Language: English
Sponsor: National Institutes of Health (DHHS); W.K. Kellogg Foundation; American Statistical Association; Mathematical Association of America; Association for Computing Machinery (ACM)
Authoring Institution: National Academies, National Academy of Sciences; National Academies, National Academy of Engineering; National Academies, National Academy of Medicine
Grant or Contract Numbers: HHSN263201200074I
Author Affiliations: N/A