在一个会话中用三种不同的语言教授查询编程是否可行?:关于面向模式的教程和小抄的研究

Lovisa Sundin, Q. Cutts
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引用次数: 7

摘要

科学专业的本科生和研究生越来越希望使用R、SQL和Python进行数据分析。这就要求教师开发资源,让学生快速上手。本研究提出并评估了一种学习设计:(1)使用面向模式的教程来教授与语言无关的关键操作,以实现数据分析查询;(2)使用小抄表来显示这些操作如何映射到特定于语言的语法。评估研究(N=21)得出的结论是,使用这种方法,三分之二的抽样数据科学新手可以在两小时内用上述所有语言实现简单到中等复杂的查询。此外,排列测试还产生了语言的显著主要影响,SQL在准确性方面排名最高。这些结果构成了关于面向模式的辅助加速数据科学教学的优点和依赖于语言的可行性的一般性讨论的一部分。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Is it feasible to teach query programming in three different languages in a single session?: A study on a pattern-oriented tutorial and cheat sheets
Undergraduates and postgraduates in science subjects are increasingly expected to conduct their data analyses using R, SQL and Python. This requires of instructors to develop resources that get students up and running quickly. This study presents and evaluates a learning design that (1) uses a pattern-oriented tutorial to teach language-independent key operations for implementing data analytic queries, and (2) uses cheat sheets to show how these operations map onto language-specific syntax. The evaluation study (N=21) concludes that using this approach, two thirds of the data science novices sampled could implement simple to moderately complex queries in all the aforementioned languages within two hours. A permutation test moreover produced a significant main effect of language, with SQL ranking the highest in accuracy. The results form part of a general discussion on the merits and language-dependent feasibility of pattern-oriented aids for accelerated data science instruction.
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