“Yes We Can!”: A Practical Approach to Teaching Reproducibility to Undergraduates
“Yes We Can!”: A Practical Approach to Teaching Reproducibility to Undergraduates
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“是的，我们可以！”：向本科生教授再现性的实用方法
DOI：
10.1162/99608f92.9e002f7b
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发表时间：
2023
期刊：
影响因子：
--
通讯作者：
Ball, Richard
中科院分区：
文献类型：
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作者：
Ball, Richard
在定量数据分析的本科生培训中包括可重复的研究方法是否可行？我们有理由相信这个问题的答案是否定的--可重复性是一个高级话题，最好留给研究生院或早期职业培训。专业标准，如AEA数据编辑（2023）指南和世界银行发展影响评估（DIME）手册（Bjarkefur等人，2021年）可能会出现太技术和复杂的介绍给本科生。即使是TIER协议（项目TIER，2023 a），这是专为各级学生访问，详细阐述了一定程度的特异性和细节，可以给教师的印象，将再现性纳入本科课程和研究监督将是一个昂贵的和破坏性的事业。1本文认为，相反，将再现性纳入本科课程是非常可行的。为了支持这一主张，我们提出了一个简单的练习，可能会分配在一个介绍性的定量方法类，然后开发四个版本的练习：一个基线，其中的问题完全忽略了可重复性，和三个后续版本，逐步引入可重复性的基本要素。学生必须为每个版本的练习获得的额外技能是适度的，但累积起来，他们准备学生在计算方法，达到最先进的标准的再现性。这些练习证明了向本科生教授再现性的可行性，并为教师提供了实现这一目标所能采取的小而实用的步骤的具体例子。表1总结了每个版本练习的主要特点。
Is it feasible to include reproducible research methods in undergraduate training in quantitative data analysis? There are reasons to believe the answer to that question is ‘no’—that reproducibility is an advanced topic best left to graduate school or early career training. Professional standards such as the AEA Data Editor’s (2023) guidelines and the World Bank Development Impact Evaluation (DIME) manual (Bjarkefur et al., 2021) may appear too technical and complex to introduce to undergraduates. Even the TIER Protocol (Project TIER, 2023a), which was designed to be accessible to students at all levels, is elaborated with a degree of specificity and detail that could give instructors the impression that incorporating reproducibility into undergraduate classes and research supervision would be a costly and disruptive undertaking. 1This essay argues that, on the contrary, integrating reproducibility into the undergraduate curriculum is eminently feasible. To support this claim, we present a simple exercise of the kind that might be assigned in an introductory quantitative methods class, and then develop four versions of the exercise: a baseline in which the issue of reproducibility is entirely neglected, and three subsequent versions that incrementally introduce essential elements of reproducibility. The additional skills students must acquire for each version of the exercise are modest, but cumulatively they prepare students in computational methods that achieve state-of-theart standards of reproducibility. These exercises demonstrate the feasibility of teaching reproducibility to undergraduates, and provide instructors with concrete examples of small, practical steps they can take to achieve that goal. The key features of each version of the exercise are summarized in Table 1.