Data Science in 2020: Computing, Curricula, and Challenges for the Next 10 Years

In the past ten years, new data science courses and programs have proliferated at the collegiate level. As faculty and administrators enter the race to provide data science training and attract new students, the road map for teaching data science remains elusive. In 2019, 69 college and university f...

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Bibliographic Details
Main Authors: Aimee Schwab-McCoy, Catherine M. Baker, Rebecca E. Gasper
Format: Article
Language:English
Published: Taylor & Francis Group 2020-11-01
Series:Journal of Statistics Education
Subjects:
Online Access:http://dx.doi.org/10.1080/10691898.2020.1851159
Description
Summary:In the past ten years, new data science courses and programs have proliferated at the collegiate level. As faculty and administrators enter the race to provide data science training and attract new students, the road map for teaching data science remains elusive. In 2019, 69 college and university faculty teaching data science courses and developing data science curricula were surveyed to learn about their curriculum, computing tools, and challenges they face in their classrooms. Faculty reported teaching a variety of computing skills in introductory data science (albeit fewer computing topics than statistics topics), and that one of the biggest challenges they face is teaching computing to a diverse audience with varying preparation. The ever-evolving nature of data science is a major hurdle for faculty teaching data science courses, and a call for more data science teaching resources was echoed in many responses.
ISSN:1069-1898