1 About the MIDFIELD workshops

midfield logo

1.1 What is midfieldr?

Analytical tools for research in student pathways are generally scarce. The R package midfieldr provides an entry to this type of intersectional research.

midfieldr is a R package that provides functions for turning student-record data into persistence metrics.

midfielddata is an R package that provides a stratified sample of the MIDFIELD data. This data package contains student records for 98,000 students, suitable for practice with the midfieldr package.

[For more information about midfieldr]
[For more information about midfielddata]

1.2 Why R?

R is an open source language and environment for statistical computing and graphics (R Core Team, 2018), ranked by IEEE in 2018 as the 7th most popular programming language (Python, C++, and Java are the top three) (Cass, 2018). If you are new to R, some of its best features, paraphrasing Wickham (2014), are:

  • R is free, open source, and available on every major platform, making it easy for others to replicate your work.
  • More than 14,250 open-source R packages are available (14,250). Many are cutting-edge tools.
  • R packages provide deep-seated support for data analysis, e.g., missing values, data frames, and subsetting.
  • R packages provide powerful tools for communicating results via html, pdf, docx, or interactive websites.
  • It is easy to get help from experts in the R community.

RStudio, an integrated development environment (IDE) for R, includes a console, editor, and tools for plotting, history, debugging, and workspace management as well as access to GitHub for collaboration and version control (RStudio Team, 2016).

[For more information about R]
[For more information about RStudio]


▲ top of page

1.3 Why R graphics?

Charles Kostelnick (2007) writes, “The array of design options in software like Microsoft Excel and PowerPoint creates the illusion of flexibility. … So marvelously malleable are these graphical effects—but for whom and to what end? Paradoxically, then, even as the technology for visualizing data has become more sophisticated, it does not necessarily engender rhetorically sensitive design.”

The graphics tools in R provide the means to control every pixel in the service of “rhetorically sensitive design.” Designers can craft their visual arguments to balance logos, ethos, pathos, and kairos as appropriate for a given audience in a given rhetorical situation.

[For a gallery of R graphics]


▲ top of page