« Previous: 12 Meeting #11: Data Science Education at Two-Year Colleges

Page 179 Cite

Suggested Citation:"References." 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. doi: 10.17226/25804.

References

ACM (Association for Computing Machinery). 2018. Lighting the Path from Community College to Computing Careers. https://www.acm.org/binaries/content/assets/education/lighting-the-path-from-community-college-to-computing-careers.pdf.

Angwin, J., J. Larson, S. Mattu, and L. Kirchner. “Machine Bias.” ProPublica, May 23. https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing.

Baker, M. 2016. “1,500 Scientists Lift the Lid on Reproducibility.” News Feature. Nature. May 25. https://www.nature.com/news/1-500-scientists-lift-the-lid-on-reproducibility-1.19970.

Barone, L., J. Williams, and D. Micklos. 2017. Unmet needs for analyzing biological big data: A survey of 704 NSF principal investigators. PLoS Computational Biology 13(10): e1005755. https://doi.org/10.1371/journal.pcbi.1005755.

Bloom, B.S. 1956. Taxonomy of Educational Objectives: The Classification of Educational Goals. White Plains, NY: Longman.

Buckheit, J.B., and D.L. Donoho. “WaveLab and Reproducible Research.” https://statweb.stanford.edu/~wavelab/Wavelab_850/wavelab.pdf.

CCC (Computing Community Consortium). 2015. “The Future of Computing Research: Industry–Academic Collaborations.” Volume 2. https://cra.org/ccc/wp-content/uploads/sites/2/2016/06/15125-CCC-Industry-Whitepaper-v4-1.pdf.

CCC. 2019. “Evolving Academia/Industry Relations in Computing Research: Interim Report.” https://www.cccblog.org/wp-content/uploads/2019/03/Industry-Interim-Report-w-footnotes.pdf.

Chapman, P., J. Clinton, R. Kerber, T. Khabaza, T. Reinartz, C. Shearer, and R. Wirth. 2000. “CRISP-DM 1.0: Step-By-Step Data Mining Guide.” https://www.the-modeling-agency.com/crisp-dm.pdf.

CMU (Carnegie Mellon University). 2017. “Carnegie Mellon University Educational Project Agreement.” https://www.ri.cmu.edu/wp-content/uploads/2017/01/Educational-Project-Agreement.pdf.

Conway, D. 2010. “The Data Science Venn Diagram.” http://drewconway.com/zia/2013/3/26/the-data-science-venn-diagram.

Page 180 Cite

Cramer, C., M. Porter, H. Sayama, L. Sheetz, and S. Uzzo. 2015. “Network Literacy: Essential Concepts and Core Ideas.” http://tinyurl.com/networkliteracy.

Dieterich, W., C. Mendoz, and T. Brennan. 2016. “COMPAS Risk Scales: Demonstrating Accuracy Equity and Predictive Parity.” Northpointe, Inc., Research Department. https://www.documentcloud.org/documents/2998391-ProPublica-Commentary-Final-070616.html.

Dwork, C., F. McSherry, K. Nissim, and A. Smith. “Calibrating Noise to Sensitivity in Private Data Analysis.” In Theory of Cryptography (S. Halevi and T. Rabin, eds.). TCC 2006. Lecture Notes in Computer Science 3876. Berlin, Heidelberg: Springer.

EDC (Education Development Center, Inc.). 2017. “Tools for Building a Big Data Career Pathway.” http://oceansofdata.org/sites/oceansofdata.org/files/Tools%20for%20Building%20a%20Big%20Data%20Career%20Path.pdf.

FTC (Federal Trade Commission). 1998. Privacy Online: A Report to Congress. https://www.ftc.gov/sites/default/files/documents/reports/privacy-online-report-congress/priv-23a.pdf.

Gould, R., R. Peck, J. Hanson, N. Horton, B. Kotz, K. Kubo, J. Malyn-Smith, M. Rudis, B. Thompson, M.D. Ward, and R. Wong. 2018. The Two-Year College Data Science Summit: A Report on NSF DUE-1735199. https://www.amstat.org/asa/files/pdfs/2018TYCDS-Final-Report.pdf.

Ioannidis, J.P.A. 2005. Why most published research findings are false. PLoS Medicine 2(8):e124. https://doi.org/10.1371/journal.pmed.0020124.

Levy, R., R. Laugesen, and F. Santosa. 2018. Big Jobs Guide. Philadelphia, PA: Society for Industrial and Applied Mathematics.

Meyer, M., A. Cimpian, and S.J. Leslie. 2015. Women are underrepresented in fields where success is believed to require brilliance. Frontiers in Psychology 6:235.

Microsoft Azure. 2017. “What Is the Team Data Science Process?” https://docs.microsoft.com/en-us/azure/machine-learning/team-data-science-process/overview.

NAE (National Academy of Engineering). 2016. Infusing Ethics into the Development of Engineers. Washington, DC: The National Academies Press.

NASEM (National Academies of Sciences, Engineering, and Medicine). 2018a. Graduate STEM Education for the 21st Century. Washington, DC: The National Academies Press.

NASEM. 2018b. Data Science for Undergraduates: Opportunities and Options. Washington, DC: The National Academies Press.

NRC (National Research Council). 2011. A Framework for K-12 Science Education. Washington, DC: The National Academies Press.

NSF (National Science Foundation). 2015. Social, Behavioral, and Economic Sciences Perspectives on Robust and Reliable Science. Report of the Subcommittee on Replicability in Science Advisory Committee to the National Science Foundation Directorate for Social, Behavioral, and Economic Sciences. May.

ODI (Oceans of Data Institute). 2014. Profile of a Big-Data-Enabled Specialist. Waltham, MA: Education Development Center, Inc.

ODI. 2016. Profile of the Data Practitioner. Waltham, MA: Education Development Center, Inc.

Patil, D.J., H. Mason, and M. Loukides. 2018. Ethics and Data Science. Sebastopol, CA: O’Reilly Media.

Patterson, D. 2014. How to build a bad research center. Communications of the ACM 57(3):33–36.

Rawlings-Goss, R., L. Cassel, M. Cragin, C. Cramer, A. Dingle, S. Friday-Stroud, A. Herron, et al. 2018. “Keeping Data Science Broad: Negotiating the Digital and Data Divide.” https://drive.google.com/file/d/14l_PGq4AxOP9fhJbKqA2necsJZ-gdiKV/view.

Zweben, S., and B. Bizot. 2018. “2017 CRA Taulbee Survey.” https://cra.org/crn/2018/05/2017-cra-taulbee-survey-another-year-of-record-undergrad-enrollment-doctoral-degree-production-steady-while-masters-production-rises-again/.