可重复教学的工具与建议
Tools and Recommendations for Reproducible Teaching
AI总结：
本文提出数据科学教师应在教学中采用可重复工作流，以计算可重复性、文档记录和开放性为三大支柱，并分享相关工具与建议。
摘要：
建议数据科学的教师-学者在研究中采用可重复工作流，并向学生传授可重复工作流。在本文中，我们提出可重复性实践的第三个维度，并建议无论是否在课程中教授可重复性，数据科学教师都应在其自身教学中采用可重复工作流。我们将计算可重复性、文档记录和开放性视为可重复教学框架的三大支柱。我们分享了针对这三大支柱的工具、示例和建议。
英文摘要：
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 paper, 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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
