Comparison of beginning R students' perceptions of peer-made plots created in two plotting systems: a randomized experiment.

IF 2.2 Q3 Social Sciences
Journal of Statistics Education Pub Date : 2020-01-01 Epub Date: 2019-12-23 DOI:10.1080/10691898.2019.1695554
Leslie Myint, Aboozar Hadavand, Leah Jager, Jeffrey Leek
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引用次数: 5

Abstract

We performed an empirical study of the perceived quality of scientific graphics produced by beginning R users in two plotting systems: the base graphics package ("base R") and the ggplot2 add-on package. In our experiment, students taking a data science course on the Coursera platform were randomized to complete identical plotting exercises using either base R or ggplot2. This exercise involved creating two plots: one bivariate scatterplot and one plot of a multivariate relationship that necessitated using color or panels. Students evaluated their peers on visual characteristics key to clear scientific communication, including plot clarity and sufficient labeling. We observed that graphics created with the two systems rated similarly on many characteristics. However, ggplot2 graphics were generally perceived by students to be slightly more clear overall with respect to presentation of a scientific relationship. This increase was more pronounced for the multivariate relationship. Through expert analysis of submissions, we also find that certain concrete plot features (e.g., trend lines, axis labels, legends, panels, and color) tend to be used more commonly in one system than the other. These observations may help educators emphasize the use of certain plot features targeted to correct common student mistakes.

初学R的学生对两种绘图系统中同伴绘制的绘图的感知比较:一个随机实验。
我们对两个绘图系统(基本图形包(“base R”)和ggplot2附加包)中初学R的用户所生成的科学图形的感知质量进行了实证研究。在我们的实验中,在Coursera平台上学习数据科学课程的学生被随机分配使用base R或ggplot2完成相同的绘图练习。这个练习包括创建两个图:一个双变量散点图和一个需要使用颜色或面板的多变量关系图。学生们根据清晰科学交流的关键视觉特征来评估他们的同伴,包括情节清晰和足够的标签。我们观察到,这两种系统所创造的图像在许多特征上都是相似的。然而,学生们普遍认为ggplot2图形在科学关系的呈现方面总体上略显清晰。这种增加在多变量关系中更为明显。通过对提交的专家分析,我们还发现某些具体的绘图特征(例如,趋势线、轴标签、图例、面板和颜色)往往在一个系统中比在另一个系统中更常用。这些观察可能有助于教育工作者强调使用特定的情节特征来纠正学生的常见错误。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Statistics Education
Journal of Statistics Education EDUCATION, SCIENTIFIC DISCIPLINES-
CiteScore
1.20
自引率
0.00%
发文量
0
审稿时长
12 weeks
期刊介绍: The "Datasets and Stories" department of the Journal of Statistics Education provides a forum for exchanging interesting datasets and discussing ways they can be used effectively in teaching statistics. This section of JSE is described fully in the article "Datasets and Stories: Introduction and Guidelines" by Robin H. Lock and Tim Arnold (1993). The Journal of Statistics Education maintains a Data Archive that contains the datasets described in "Datasets and Stories" articles, as well as additional datasets useful to statistics teachers. Lock and Arnold (1993) describe several criteria that will be considered before datasets are placed in the JSE Data Archive.
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