Comparison of Beginning R Students' Perceptions of Peer-Made Plots Created in Two Plotting Systems: A Randomized Experiment. Issue 1 (2nd January 2020)
- Record Type:
- Journal Article
- Title:
- Comparison of Beginning R Students' Perceptions of Peer-Made Plots Created in Two Plotting Systems: A Randomized Experiment. Issue 1 (2nd January 2020)
- Main Title:
- Comparison of Beginning R Students' Perceptions of Peer-Made Plots Created in Two Plotting Systems: A Randomized Experiment
- Authors:
- Myint, Leslie
Hadavand, Aboozar
Jager, Leah
Leek, Jeffrey - Abstract:
- 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. Supplementary materials for this article are available online.
- Is Part Of:
- Journal of statistics education. Volume 28:Issue 1(2020)
- Journal:
- Journal of statistics education
- Issue:
- Volume 28:Issue 1(2020)
- Issue Display:
- Volume 28, Issue 1 (2020)
- Year:
- 2020
- Volume:
- 28
- Issue:
- 1
- Issue Sort Value:
- 2020-0028-0001-0000
- Page Start:
- 98
- Page End:
- 108
- Publication Date:
- 2020-01-02
- Subjects:
- Assessment -- Data science -- Data visualization -- R -- Randomized trial -- Statistical perception
Statistics -- Study and teaching -- Periodicals
Statistics -- Study and teaching
Periodicals
519.5071 - Journal URLs:
- http://ww2.amstat.org/publications/jse/ ↗
http://tandfonline.com/loi/ujse20 ↗
http://www.tandfonline.com/ ↗ - DOI:
- 10.1080/10691898.2019.1695554 ↗
- Languages:
- English
- ISSNs:
- 1069-1898
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 13694.xml