Writing goals in U.S. undergraduate data science course outlines: A textual analysis

IF 0.8 Q2 EDUCATION & EDUCATIONAL RESEARCH Teaching Statistics Pub Date : 2022-08-01 DOI:10.1111/test.12314
Constance L. Gooding, Alex Lyford, G. Giaimo
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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.
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美国本科生数据科学课程大纲的写作目标:文本分析
高等教育机构的讲师们设计了无数的数据科学课程,以跟上大数据的兴起。企业和公司越来越有兴趣雇佣具有强大数据采集、管理和沟通技能的人员。由于数据科学作为一个研究领域相对较新,尽管它与统计研究有着深厚的联系,但很少对数据科学的课程、专业、项目和课程目标进行全面分析。通过这项研究,我们分析了美国本科生数据科学课是如何教授写作和沟通的。我们从课程描述和教学大纲中分析了写作和交际学习目标的存在。这些结果表明,大多数数据科学课程都强调技术、计算技能而非写作和沟通技能。最后,我们提出了一套可行的启发式方法,强调将写作和沟通融入数据科学课程,以便学生准备好作为负责任的公民使用这些技能。
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来源期刊
Teaching Statistics
Teaching Statistics EDUCATION & EDUCATIONAL RESEARCH-
CiteScore
2.10
自引率
25.00%
发文量
31
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