Undergraduate data science degrees emphasize computer science and statistics but fall short in ethics training and domain-specific context
Affiliation
Office of Digital Innovation & Stewardship, University Libraries, University of ArizonaDepartment of Educational Policy Studies and Practice, University of Arizona
Issue Date
2021-03-25
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Oliver JC, McNeil T. 2021. Undergraduate data science degrees emphasize computer science and statistics but fall short in ethics training and domain-specific context. PeerJ Computer Science 7:e441.Journal
PeerJ Computer ScienceRights
Copyright © 2021 Oliver and McNeil. This is an open access article distributed under the terms of the Creative Commons Attribution License.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
The interdisciplinary field of data science, which applies techniques from computer science and statistics to address questions across domains, has enjoyed recent considerable growth and interest. This emergence also extends to undergraduate education, whereby a growing number of institutions now offer degree programs in data science. However, there is considerable variation in what the field actually entails and, by extension, differences in how undergraduate programs prepare students for data-intensive careers. We used two seminal frameworks for data science education to evaluate undergraduate data science programs at a subset of 4-year institutions in the United States; developing and applying a rubric, we assessed how well each program met the guidelines of each of the frameworks. Most programs scored high in statistics and computer science and low in domain-specific education, ethics, and areas of communication. Moreover, the academic unit administering the degree program significantly influenced the course-load distribution of computer science and statistics/mathematics courses. We conclude that current data science undergraduate programs provide solid grounding in computational and statistical approaches, yet may not deliver sufficient context in terms of domain knowledge and ethical considerations necessary for appropriate data science applications. Additional refinement of the expectations for undergraduate data science education is warranted.Note
Open access journalEISSN
2376-5992Version
Final published versionae974a485f413a2113503eed53cd6c53
10.7717/peerj-cs.441
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Except where otherwise noted, this item's license is described as Copyright © 2021 Oliver and McNeil. This is an open access article distributed under the terms of the Creative Commons Attribution License.