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Suggested Citation:"Front Matter." 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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Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

PREPUBLICATION COPY—SUBJECT TO FURTHER EDITORIAL CORRECTION DATA SCIENCE FOR UNDERGRADUATES: OPPORTUNITIES AND OPTIONS Committee on Envisioning the Data Science Discipline: The Undergraduate Perspective Computer Science and Telecommunications Board Board on Mathematical Sciences and Analytics Committee on Applied and Theoretical Statistics Division on Engineering and Physical Sciences Board on Science Education Division of Behavioral and Social Sciences and Education A Consensus Study Report of

THE NATIONAL ACADEMIES PRESS 500 Fifth Street, NW Washington, DC 20001 This activity was supported by Award No. 1626983 from the National Science Foundation (Directorate for Computer and Information Science and Engineering; Directorate for Education and Human Resources; Directorate for Mathematical and Physical Sciences/Division of Mathematical Sciences; and Directorate for Social, Behavioral and Economic Sciences). Any opinions, findings, conclusions, or recommendations expressed in this publication do not necessarily reflect the views of any organization or agency that provided support for the project. International Standard Book Number-13: _________________ International Standard Book Number-10: _________________ Digital Object Identifier: https://doi.org/10.17226/25104 Additional copies of this publication are available for sale from the National Academies Press, 500 Fifth Street, NW, Keck 360, Washington, DC 20001; (800) 624-6242 or (202) 334-3313; http:// www.nap.edu. Copyright 2018 by the National Academy of Sciences. All rights reserved. Printed in the United States of America Suggested citation: National Academies of Sciences, Engineering, and Medicine. 2018. Data Science for Undergraduates: Opportunities and Options. Washington, DC: The National Academies Press. https://doi.org/10.17226/25104. PREPUBLICATION COPY—SUBJECT TO FURTHER EDITORIAL CORRECTION

The National Academy of Sciences was established in 1863 by an Act of Congress, signed by President Lincoln, as a private, nongovernmental institution to advise the nation on issues related to science and technology. Members are elected by their peers for outstanding contributions to research. Dr. Marcia McNutt is president. The National Academy of Engineering was established in 1964 under the charter of the National Academy of Sciences to bring the practices of engineering to advising the nation. Members are elected by their peers for extraordinary contributions to engineering. Dr. C. D. Mote, Jr., is president. The National Academy of Medicine (formerly the Institute of Medicine) was established in 1970 under the charter of the National Academy of Sciences to advise the nation on medical and health issues. Members are elected by their peers for distinguished contributions to medicine and health. Dr. Victor J. Dzau is president. The three Academies work together as the National Academies of Sciences, Engineering, and Medicine to provide independent, objective analysis and advice to the nation and conduct other activities to solve complex problems and inform public policy decisions. The National Academies also encourage education and research, recognize outstanding contributions to knowledge, and increase public understanding in matters of science, engineering, and medicine. Learn more about the National Academies of Sciences, Engineering, and Medicine at www.nationalacademies.org. PREPUBLICATION COPY—SUBJECT TO FURTHER EDITORIAL CORRECTION

Consensus Study Reports published by the National Academies of Sciences, Engineering, and Medicine document the evidence-based consensus on the study’s statement of task by an authoring committee of experts. Reports typically include findings, conclusions, and recommendations based on information gathered by the committee and the committee’s deliberations. Each report has been subjected to a rigorous and independent peer-review process and it represents the position of the National Academies on the statement of task. Proceedings published by the National Academies of Sciences, Engineering, and Medicine chronicle the presentations and discussions at a workshop, symposium, or other event convened by the National Academies. The statements and opinions contained in proceedings are those of the participants and are not endorsed by other participants, the planning committee, or the National Academies. For information about other products and activities of the National Academies, please visit www.nationalacademies.org/about/whatwedo. PREPUBLICATION COPY—SUBJECT TO FURTHER EDITORIAL CORRECTION

COMMITTEE ON ENVISIONING THE DATA SCIENCE DISCIPLINE: THE UNDERGRADUATE PERSPECTIVE LAURA HAAS, NAE, 1 University of Massachusetts Amherst, Co-Chair ALFRED O. HERO III, University of Michigan, Co-Chair ANI ADHIKARI, University of California, Berkeley DAVID CULLER, NAE, University of California, Berkeley DAVID DONOHO, NAS, 2 Stanford University E. THOMAS EWING, Virginia Tech LOUIS J. GROSS, University of Tennessee, Knoxville NICHOLAS J. HORTON, Amherst College JULIA LANE, New York University ANDREW MCCALLUM, University of Massachusetts Amherst RICHARD MCCULLOUGH, Harvard University REBECCA NUGENT, Carnegie Mellon University LEE RAINIE, Pew Research Center ROB RUTENBAR, University of Pittsburgh KRISTIN TOLLE, Microsoft Research TALITHIA WILLIAMS, Harvey Mudd College ANDREW ZIEFFLER, University of Minnesota, Minneapolis Staff MICHELLE K. SCHWALBE, Director, Board on Mathematical Sciences and Analytics (BMSA), Study Director JON EISENBERG, Director, Computer Science and Telecommunications Board (CSTB) BEN WENDER, Director, Committee on Applied and Theoretical Statistics AMY STEPHENS, Program Officer, Board on Science Education LINDA CASOLA, BMSA, Associate Program Officer and Editor RENEE HAWKINS, CSTB, Financial Manager JANKI PATEL, CSTB, Senior Program Assistant 1 Member, National Academy of Engineering. 2 Member, National Academy of Sciences. v PREPUBLICATION COPY—SUBJECT TO FURTHER EDITORIAL CORRECTION

COMPUTER SCIENCE AND TELECOMMUNICATIONS BOARD FARNAM JAHANIAN, Carnegie Mellon University, Chair LUIZ ANDRE BARROSO, Google, Inc. STEVEN M. BELLOVIN, NAE, 1 Columbia University ROBERT F. BRAMMER, Brammer Technology, LLC DAVID CULLER, NAE, University of California, Berkeley EDWARD FRANK, Cloud Parity, Inc. LAURA HAAS, NAE, University of Massachusetts Amherst MARK HOROWITZ, NAE, Stanford University ERIC HORVITZ, NAE, Microsoft Corporation VIJAY KUMAR, NAE, University of Pennsylvania BETH MYNATT, Georgia Institute of Technology CRAIG PARTRIDGE, Raytheon BBN Technologies DANIELA RUS, NAE, Massachusetts Institute of Technology FRED B. SCHNEIDER, NAE, Cornell University MARGO SELTZER, Harvard University MOSHE VARDI, NAS 2/NAE, Rice University Staff JON EISENBERG, Director LYNETTE I. MILLETT, Associate Director EMILY GRUMBLING, Program Officer KATIRIA ORTIZ, Associate Program Officer RENEE HAWKINS, Financial and Administrative Manager JANKI PATEL, Senior Program Assistant SHENAE BRADLEY, Administrative Assistant 1 Member, National Academy of Engineering. 2 Member, National Academy of Sciences. vi PREPUBLICATION COPY—SUBJECT TO FURTHER EDITORIAL CORRECTION

BOARD ON MATHEMATICAL SCIENCES AND ANALYTICS STEPHEN M. ROBINSON, NAE, 1 University of Wisconsin, Madison, Chair JOHN R. BIRGE, NAE, University of Chicago W. PETER CHERRY, Independent Consultant DAVID CHU, Institute for Defense Analyses RONALD R. COIFMAN, NAS, 2 Yale University JAMES CURRY, University of Colorado Boulder CHRISTINE FOX, Johns Hopkins Applied Physics Laboratory MARK L. GREEN, University of California, Los Angeles PATRICIA A. JACOBS, Naval Postgraduate School JOSEPH A. LANGSAM, Morgan Stanley (Retired) SIMON A. LEVIN, NAS, Princeton University ANDREW W. LO, Massachusetts Institute of Technology DAVID MAIER, Portland State University LOIS CURFMAN MCINNES, Argonne National Laboratory FRED S. ROBERTS, Rutgers, The State University of New Jersey ELIZABETH A. THOMPSON, NAS, University of Washington CLAIRE TOMLIN, University of California, Berkeley LANCE WALLER, Emory University KAREN WILLCOX, Massachusetts Institute of Technology DAVID YAO, NAE, Columbia University Staff MICHELLE K. SCHWALBE, Director BEN WENDER, Program Officer LINDA CASOLA, Associate Program Officer and Editor BETH DOLAN, Financial Manager RODNEY N. HOWARD, Administrative Assistant 1 Member, National Academy of Engineering. 2 Member, National Academy of Sciences. vii PREPUBLICATION COPY—SUBJECT TO FURTHER EDITORIAL CORRECTION

COMMITTEE ON APPLIED AND THEORETICAL STATISTICS ALFRED O. HERO III, University of Michigan, Chair ALICIA CARRIQUIRY, NAM, 1 Iowa State University MICHAEL J. DANIELS, University of Florida KATHERINE BENNETT ENSOR, Rice University AMY HERRING, Duke University NICHOLAS J. HORTON, Amherst College DAVID MADIGAN, Columbia University JOSÉ M.F. MOURA, NAE, 2 Carnegie Mellon University NANCY REID, NAS, 3 University of Toronto CYNTHIA RUDIN, Duke University AARTI SINGH, Carnegie Mellon University Staff BEN WENDER, Director LINDA CASOLA, Associate Program Officer and Editor BETH DOLAN, Financial Manager RODNEY N. HOWARD, Administrative Assistant 1 Member, National Academy of Medicine. 2 Member, National Academy of Engineering. 3 Member, National Academy of Sciences. viii PREPUBLICATION COPY—SUBJECT TO FURTHER EDITORIAL CORRECTION

BOARD ON SCIENCE EDUCATION ADAM GAMORAN, William T. Grant Foundation, Chair SUNITA V. COOKE, MiraCosta College MELANIE COOPER, Michigan State University RODOLFO DIRZO, NAS, 1 Stanford University RUSH D. HOLT, American Association for the Advancement of Science MATTHEW KREHBIEL, Achieve, Inc. MICHAEL LACH, University of Chicago LYNN LIBEN, Pennsylvania State University CATHRYN (CATHY) MANDUCA, Carleton College JOHN MATHER, NAS, NASA Goddard Space Flight Center TONYA M. MATTHEWS, Michigan Science Center BRIAN REISER¸ Northwestern University MARSHALL (MIKE) SMITH, Carnegie Foundation for the Advancement of Teaching ROBERTA TANNER, Thompson School District (Retired) SUZANNE WILSON, Michigan State University Staff HEIDI SCHWEINGRUBER, Director KERRY BRENNER, Senior Program Officer MARGARET HILTON, Senior Program Officer KENNE DIBNER, Program Officer AMY STEPHENS, Program Officer MATTHEW LAMMERS, Program Coordinator LETICIA GARCILAZO GREEN, Senior Program Assistant MARGARET KELLY, Senior Program Assistant COREETHA ENTZMINGER, Program Assistant 1 Member, National Academy of Sciences. ix PREPUBLICATION COPY—SUBJECT TO FURTHER EDITORIAL CORRECTION

PREPUBLICATION COPY—SUBJECT TO FURTHER EDITORIAL CORRECTION

Acknowledgments This Consensus Study Report has been reviewed in draft form by individuals chosen for their diverse perspectives and technical expertise. The purpose of this independent review is to provide candid and critical comments that will assist the National Academies of Sciences, Engineering, and Medicine in making each published report as sound as possible and to ensure that it meets the institutional standards for quality, objectivity, evidence, and responsiveness to the study charge. The review comments and draft manuscript remain confidential to protect the integrity of the deliberative process. We thank the following individuals for their review of this report: Richard (Dick) De Veaux, Williams College, Natalie M. Evans Harris, BrightHive, Charles Isbell, Jr., Georgia Institute of Technology, Iain Johnstone, NAS, 1 Stanford University, Brian Kotz, Montgomery College, Peter Norvig, Google, Inc., Renata Rawlings-Goss, South Big Data Regional Innovation Hub, Ali Sayed, NAE, 2 University of California, Los Angeles, Margo Seltzer, Harvard University, and Sharon Wood, NAE, University of Texas, Austin. Although the reviewers listed above provided many constructive comments and suggestions, they were not asked to endorse the conclusions or recommendations presented in the report, nor did they see the final draft of the report before its release. The review of this report was overseen by Alicia L. Carriquiry, NAM, 3 Iowa State University. She was responsible for making certain that an independent examination of this report was carried out in accordance with the standards of the National Academies and that all review comments were carefully considered. Responsibility for the final content of this report rests entirely with the authoring committee and the National Academies. The committee would like to thank Andy Burnett from Knowinnovation for facilitating the committee’s May 2017 workshop as well as the following staff members from the National Science 1 Member, National Academy of Sciences. 2 Member, National Academy of Engineering. 3 Member, National Academy of Medicine. xi

Foundation for their input, assistance, and support of this study: Stephanie August, Chaitan Baru, Eva Campo, Vandana Janeja, Nandini Kannan, Sara Kiesler, Gabriel Perez-Giz, Earnestine Psalmonds-Easter, and Elena Zheleva. The committee would also like to thank the many individuals who provided input to this study; the full list of these individuals is included in Appendix C. xii

Contents PREFACE P-1 SUMMARY S-1 1 INTRODUCTION 1-1 A Look to the Future, 1-3 Report Overview, 1-4 References, 1-4 2 KNOWLEDGE FOR DATA SCIENTISTS 2-1 Data Scientists of Today and Tomorrow, 2-4 Data Acumen, 2-7 A Code of Ethics for Data Science, 2-15 References, 2-16 3 DATA SCIENCE EDUCATION 3-1 Undergraduate Modalities, 3-1 Middle and High School Education, 3-17 References, 3-18 4 STARTING A DATA SCIENCE PROGRAM 4-1 Ensuring Broad Participation, 4-2 Academic Infrastructure, 4-4 Curriculum, 4-7 Faculty Resources, 4-7 Assessment, 4-8 xiii

References, 4-8 5 EVOLUTION AND EVALUATION 5-1 Evolution, 5-2 Evaluation, 5-5 Roles for Professional Societies, 5-10 References, 5-11 6 CONCLUSIONS 6-1 APPENDIXES A Biographies of the Committee A-1 B Meetings and Presentations B-1 C Contributing Individuals C-1 D Data Science Oath D-1 xiv

Preface The National Academies of Sciences, Engineering, and Medicine established the Committee on Envisioning the Data Science Discipline: The Undergraduate Perspective to set forth a vision for the emerging discipline of data science at the undergraduate level (see Box P.1 for the committee’s statement of task). BOX P.1 Statement of Task A National Academies of Sciences, Engineering, and Medicine study will set forth a vision for the emerging discipline of data science at the undergraduate level. It will emphasize core underlying principles, intellectual content, and pedagogical issues specific to data science, including core concepts that distinguish it from neighboring disciplines. It will not consider the practicalities of creating materials, courses, or programs. It will develop this vision considering applications of and careers in data science. It will focus on the undergraduate level, addressing related issues at the middle and high school level as well as community colleges as appropriate, and will draw on experiences in creating master’s-level programs. It will also consider opportunities created by the emergence of a new science, technology, engineering, and mathematics (STEM) field to engage underrepresented student populations and consider ways to reduce the “leakage” seen in existing STEM pathways. Information gathering will center around two workshops, the first likely focused on principles and intellectual content, and the second likely focused on pedagogy and implications for middle and high schools and community colleges. To get material on the record quickly and spark community feedback, a rapporteur-authored workshop summary report will be issued following the first workshop. A final report will be issued following both workshops and committee deliberations setting forth a vision for undergraduate education in data science. This study was sponsored by the National Science Foundation. The Committee on Envisioning the Data Science Discipline: The Undergraduate Perspective (see Appendix A for biographical sketches of the committee members) conducted a number of information-gathering activities and engaged a broad community in its conversations to address the statement of task shown in Box P.1 (see Appendix B for a list of the presentations given during these meetings and Appendix C for a list of those who contributed). In December 2016, the committee met to discuss possible future directions based on progress with current data science programs; societal implications of the evolving field of data science; approaches to expand diversity and inclusion in data science among students, staff, and topic areas; and perspectives on P-1 PREPUBLICATION COPY—SUBJECT TO FURTHER EDITORIAL CORRECTION

envisioning the future of data science for undergraduates. In April 2017, the committee organized a webinar to collect further input from the public on topics of importance for this study. In May 2017, the committee convened a workshop in which participants discussed educational models to build relevant foundational, translational, and professional skills for data scientists in various roles; the use of high-impact educational practices in the delivery of data science education; and strategies for broad participation in data science education that rely on formal modes of evaluation and assessment. Participants focused on the ways in which students, institutions, and programs could change in the coming decade, as well as how these changes will affect future plans for data science education. The committee also held nine webinars throughout Fall 2017 as another means to engage the public in conversations about various aspects of data science education, which addressed the following topics: 1. Building data acumen; 2. Incorporating real-world applications; 3. Training faculty and developing curriculum; 4. Enhancing communication and teamwork skills; 5. Fostering interdepartmental collaboration and institutional organization; 6. Considering ethics; 7. Assessing and evaluating data science programs; 8. Emphasizing diversity, inclusion, and increased participation; and 9. Exploring 2-year colleges and institutional partnerships. Although these nine webinars focused specifically on applications to data science programs, many of the discussions highlighted best practices relevant for all types of academic programming. The committee met for a final session in December 2017 to prepare for the writing of this report. During this session, the committee synthesized discussions from the webinar series and results from activities under way in the data science community. This final report, which was preceded by a September 2017 interim report, explores key questions about the future of the field of data science. P-2 PREPUBLICATION COPY—SUBJECT TO FURTHER EDITORIAL CORRECTION

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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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