Tools and Recommendations for Reproducible Teaching

IF 1.5 Q2 EDUCATION, SCIENTIFIC DISCIPLINES Journal of Statistics and Data Science Education Pub Date : 2022-02-19 DOI:10.1080/26939169.2022.2138645
M. Dogucu, Mine Çetinkaya-Rundel
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引用次数: 5

Abstract

Abstract It is recommended that teacher-scholars of data science adopt reproducible workflows in their research as scholars and teach reproducible workflows to their students. In this article, we propose a third dimension to reproducibility practices and recommend that regardless of whether they teach reproducibility in their courses or not, data science instructors adopt reproducible workflows for their own teaching. We consider computational reproducibility, documentation, and openness as three pillars of reproducible teaching framework. We share tools, examples, and recommendations for the three pillars.
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可重复教学的工具和建议
建议数据科学的教师学者在他们作为学者的研究中采用可再现工作流,并向他们的学生教授可再现工作流。在本文中,我们提出了可再现性实践的第三个维度,并建议无论他们是否在课程中教授可再现性,数据科学教师都应该在自己的教学中采用可再现的工作流。我们认为计算可重复性、文档化和开放性是可重复性教学框架的三大支柱。我们将分享这三大支柱的工具、示例和建议。
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来源期刊
Journal of Statistics and Data Science Education
Journal of Statistics and Data Science Education EDUCATION, SCIENTIFIC DISCIPLINES-
CiteScore
3.90
自引率
35.30%
发文量
52
审稿时长
12 weeks
期刊最新文献
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