ERIC Number: EJ1352131
Record Type: Journal
Publication Date: 2021
Pages: 11
Abstractor: As Provided
ISBN: N/A
ISSN: N/A
EISSN: EISSN-2693-9169
Data Science in 2020: Computing, Curricula, and Challenges for the Next 10 Years
Schwab-McCoy, Aimee; Baker, Catherine M.; Gasper, Rebecca E.
Journal of Statistics and Data Science Education, v29 suppl 1 pS40-S50 2021
In the past 10 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 curricula, 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.
Descriptors: Statistics Education, Higher Education, College Students, Teaching Methods, Computation, Data Analysis, Introductory Courses, Curriculum, Resources, Programming Languages, Computer Software, Prerequisites, Required Courses
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Publication Type: Journal Articles; Reports - Research
Education Level: Higher Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A