National Academies Press: OpenBook

Data Science for Undergraduates: Opportunities and Options (2018)

Chapter: Appendix B: Meetings and Presentations

« Previous: Appendix A: Biographies of the Committee
Suggested Citation:"Appendix B: Meetings and Presentations." National Academies of Sciences, Engineering, and Medicine. 2018. Data Science for Undergraduates: Opportunities and Options. Washington, DC: The National Academies Press. doi: 10.17226/25104.
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B

Meetings and Presentations

FIRST COMMITTEE MEETING
Washington, D.C.
December 12-13, 2016

Lessons from Current Data Science Programs and Future Directions

Rebecca Nugent, Carnegie Mellon University

Rob Rutenbar, University of Illinois, Urbana-Champaign

David Culler, University of California, Berkeley

William Yslas Velez, University of Arizona

Duncan Temple Lang, University of California, Davis

Envisioning the Field of Data Science and Future Directions and Implications to Society

David Donoho, Stanford University

Lee Rainie, Pew Research Center

Expanding Diversity in Data Science—Among Student Populations and in Topic Areas Embraced by Data Science

Bhramar Mukherjee, University of Michigan

Deb Agarwal, Lawrence Berkeley National Laboratory

Andrew Zieffler, University of Minnesota

Suggested Citation:"Appendix B: Meetings and Presentations." National Academies of Sciences, Engineering, and Medicine. 2018. Data Science for Undergraduates: Opportunities and Options. Washington, DC: The National Academies Press. doi: 10.17226/25104.
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Questions That Should Be Asked to Envision the Future of Data Science for Undergraduates

Tom Ewing, Virginia Tech

Louis Gross, University of Tennessee, Knoxville

Chris Mentzel, Gordon and Betty Moore Foundation

Patrick Perry, New York University

John Abowd, U.S. Census Bureau

WEBINAR
April 25, 2017

Overview of the Study

Michelle Schwalbe, National Academies of Sciences, Engineering, and Medicine

Alfred Hero, University of Michigan

Laura Haas, IBM Almaden Research Center

Louis Gross, University of Tennessee, Knoxville

Facilitated Discussion

Andy Burnett, Knowinnovation

WORKSHOP
Washington, D.C.
May 2-3, 2017

Opening Comments

Study Co-Chairs: Laura Haas, IBM, and Alfred Hero III, University of Michigan

Comments from the National Science Foundation

Chaitan Baru, National Science Foundation

Overview of the Workshop

Andy Burnett, Knowinnovation

Workshop Themes

Skills and Knowledge for Future Data Scientists

Rob Rutenbar, University of Illinois, Urbana-Champaign

Broadening Participation in Data Science Education

Julia Lane, New York University

Suggested Citation:"Appendix B: Meetings and Presentations." National Academies of Sciences, Engineering, and Medicine. 2018. Data Science for Undergraduates: Opportunities and Options. Washington, DC: The National Academies Press. doi: 10.17226/25104.
×

Future Delivery of Data Science Education

Nicholas Horton, Amherst College

Table Discussions About Key Questions

Question Exploration Groups

Small breakout groups to discuss all three questions

Feedback from Question Groups

Present ideas and discuss questions with full group

Integrate Ideas into Three Thematic Areas

Form three groups aligned with the thematic questions or possible new questions

Feedback from Question Groups

Share the integrated ideas with the full group

Plenary Discussion of Feedback

Study Co-Chairs: Laura Haas, IBM, and Alfred Hero III, University of Michigan

New Questions and Ideas That Emerged Overnight

Full group discussion led by Andy Burnett, Knowinnovation

Identify the Most Promising Ideas and Possible Findings for the Committee’s Interim Report

Small table groups

Backcast the Most Promising Ideas

Small table groups discuss what steps would have to be taken in order to implement the most promising ideas

WEBINAR
BUILDING DATA ACUMEN
September 12, 2017

Capstone Courses

Nicole Lazar, University of Georgia

NC State University Data Initiative

Mladen Vouk, North Carolina State University

Suggested Citation:"Appendix B: Meetings and Presentations." National Academies of Sciences, Engineering, and Medicine. 2018. Data Science for Undergraduates: Opportunities and Options. Washington, DC: The National Academies Press. doi: 10.17226/25104.
×

Moderated Discussion

Tom Ewing, Virginia Tech

WEBINAR
INCORPORATING REAL-WORLD EXAMPLES
September 19, 2017

Using Urban and Sports Data in Student Projects

Cláudio Silva, New York University

Building a Talent Pipeline Through a Strategic Career Development Program and Academic-Industrial Partnership

Sears Merritt, MassMutual Financial Group

Moderated Discussion

Tom Ewing, Virginia Tech

WEBINAR
FACULTY TRAINING AND CURRICULUM DEVELOPMENT
September 26, 2017

Go to the People: Impactful Faculty Training in Data Science

Michael Posner, Villanova University

Shodor, National Computational Science Institute, XSEDE, and Blue Waters—How Can We Help?

Bob Panoff, Shodor Education Foundation

Moderated Discussion

Nicholas Horton, Amherst College

WEBINAR
COMMUNICATION SKILLS AND TEAMWORK
October 3, 2017

The Imperative of Interdisciplinarity in Data Science

Madeleine Clare Elish, Data and Society Research Institute

Data Science Collaboration for Public-Facing Research

Adam Hughes, Pew Research Center

Moderated Discussion

Lee Rainie, Pew Research

Suggested Citation:"Appendix B: Meetings and Presentations." National Academies of Sciences, Engineering, and Medicine. 2018. Data Science for Undergraduates: Opportunities and Options. Washington, DC: The National Academies Press. doi: 10.17226/25104.
×

WEBINAR
INTERDEPARTMENTAL COLLABORATION AND
INSTITUTIONAL ORGANIZATION
October 10, 2017

Forging Virginia Tech’s Computational Modeling and Data Analytics (CMDA) Major Across Departments

Mark Embree, Virginia Tech

Some Thoughts on Data Science Education for Undergraduates

Mike Franklin, University of Chicago

Moderated discussion

Tom Ewing, Virginia Tech

WEBINAR
ETHICS
October 17, 2017

An Ethical Reasoning Framework for Data Science Education

Sorin Adam Matei, Purdue University

Ethical Thinking for Data Science Education

Brittany Fiore-Gartland, University of Washington

Moderated Discussion

Lee Rainie, Pew Research

WEBINAR
ASSESSMENT AND EVALUATION FOR
DATA SCIENCE PROGRAMS
October 24, 2017

Evaluation of Data Science Programs

Pamela Bishop, University of Tennessee, Knoxville

Assessing Data Science Learning Outcomes

Kari Jordan, Data Carpentry

Moderated Discussion

Louis Gross, University of Tennessee, Knoxville

Suggested Citation:"Appendix B: Meetings and Presentations." National Academies of Sciences, Engineering, and Medicine. 2018. Data Science for Undergraduates: Opportunities and Options. Washington, DC: The National Academies Press. doi: 10.17226/25104.
×

WEBINAR
DIVERSITY, INCLUSION, AND INCREASING PARTICIPATION
November 7, 2017

Diversity, Inclusion, and Increasing Participation in Data Science

Allison Master, University of Washington

Diversity and Inclusion in Data Science: Using Data-Informed Decisions to Drive Student Success

Talithia Williams, Harvey Mudd College

Moderated Discussion

Nicholas Horton, Amherst College

WEBINAR
2-YEAR COLLEGES AND INSTITUTIONAL PARTNERSHIPS
November 14, 2017

Developing a 2-year College Certificate Program in Data Science

Brian Kotz, Montgomery College

Data Analytics Certificate Program at JCCC

Suzanne Smith, Johnson County Community College

Moderated Discussion

Laura Haas, University of Massachusetts Amherst

SECOND COMMITTEE MEETING
Washington, D.C.
December 6-7, 2017

Webinar Recaps

Tom Ewing, Virginia Tech

Nicholas Horton, Amherst College

Lee Rainie, Pew Research

Louis Gross, University of Tennessee, Knoxville

Laura Haas, University of Massachusetts Amherst

Big Data Hubs

Melissa Cragin, Midwest Big Data Hub

Renata Rawlings-Goss, South Big Data Hub

Comments from the National Science Foundation

Stephanie August, National Science Foundation

Chaitan Baru, National Science Foundation

Suggested Citation:"Appendix B: Meetings and Presentations." National Academies of Sciences, Engineering, and Medicine. 2018. Data Science for Undergraduates: Opportunities and Options. Washington, DC: The National Academies Press. doi: 10.17226/25104.
×
Page 105
Suggested Citation:"Appendix B: Meetings and Presentations." National Academies of Sciences, Engineering, and Medicine. 2018. Data Science for Undergraduates: Opportunities and Options. Washington, DC: The National Academies Press. doi: 10.17226/25104.
×
Page 106
Suggested Citation:"Appendix B: Meetings and Presentations." National Academies of Sciences, Engineering, and Medicine. 2018. Data Science for Undergraduates: Opportunities and Options. Washington, DC: The National Academies Press. doi: 10.17226/25104.
×
Page 107
Suggested Citation:"Appendix B: Meetings and Presentations." National Academies of Sciences, Engineering, and Medicine. 2018. Data Science for Undergraduates: Opportunities and Options. Washington, DC: The National Academies Press. doi: 10.17226/25104.
×
Page 108
Suggested Citation:"Appendix B: Meetings and Presentations." National Academies of Sciences, Engineering, and Medicine. 2018. Data Science for Undergraduates: Opportunities and Options. Washington, DC: The National Academies Press. doi: 10.17226/25104.
×
Page 109
Suggested Citation:"Appendix B: Meetings and Presentations." National Academies of Sciences, Engineering, and Medicine. 2018. Data Science for Undergraduates: Opportunities and Options. Washington, DC: The National Academies Press. doi: 10.17226/25104.
×
Page 110
Next: Appendix C: Contributing Individuals »
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Data science is emerging as a field that is revolutionizing science and industries alike. Work across nearly all domains is becoming more data driven, affecting both the jobs that are available and the skills that are required. As more data and ways of analyzing them become available, more aspects of the economy, society, and daily life will become dependent on data. It is imperative that educators, administrators, and students begin today to consider how to best prepare for and keep pace with this data-driven era of tomorrow. Undergraduate teaching, in particular, offers a critical link in offering more data science exposure to students and expanding the supply of data science talent.

Data Science for Undergraduates: Opportunities and Options offers a vision for the emerging discipline of data science at the undergraduate level. This report outlines some considerations and approaches for academic institutions and others in the broader data science communities to help guide the ongoing transformation of this field.

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