Writing goals in U.S. undergraduate data science course outlines: A textual analysis. (1st August 2022)

• Record Type: Journal Article
• Authors: Gooding, Constance L.; Lyford, Alex; Giaimo, Genie N.
• Is Part Of: Teaching statistics. Volume 44:Number 3(2022)
• Page Start: 110
• Page End: 118
• Publication Date: 2022-08-01
• Subjects: teaching -- communication -- data science -- text analysis -- undergraduate -- writing; Statistics -- Study and teaching (Elementary) -- Periodicals; Statistics -- Study and teaching (Secondary) -- Periodicals; 373
• DOI: 10.1111/test.12314
• Languages: English
• ISSNs: 0141-982X

Abstract

Abstract: Instructors at postsecondary institutions have designed a myriad of data science classes to keep up with the rise of big data. Businesses and companies have become increasingly interested in hiring people with strong data acquisition, management, and communication skills. Since data science as a field of study is relatively new, though it has deep connections to statistical studies, there are few comprehensive analyses of data science classes, majors, programs, and curricular goals. Through this research, we analyze how writing and communication are taught in undergraduate data science classes in the United States. We analyze the presence of writing and communication learning goals from course descriptions and course syllabi. These results show that most data science courses emphasize technical, computing skills over writing, and communication skills. We conclude with a set of actionable heuristics that emphasize integrating writing and communication into data science courses so that students are prepared to use these skills as responsible citizens.