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Overview

midfielddata is an R data package that provides anonymized student-level records for 98,000 undergraduates at three US institutions from 1988 through 2018, collected in four data tables keyed by student ID:

  • student   all students, their demographics, transfer status, institution, etc.
  • course   all students, every course, course name, number, credit hours, grades, etc.
  • term   all students, every term, program, standing, GPA, etc.
  • degree   all graduating students, their degree(s), program(s), term

The data in midfielddata are a proportionate stratified sample of the MIDFIELD database (Ohland and Long 2016), but are not suitable for drawing inferences about program attributes or student experiences—midfielddata are for practice, not research.

Suggested packages.

Installation

The installed size of midfielddata is about 24 Mb, so installation will take longer than that of a conventional CRAN package. Install from the MIDFIELDR drat repository with:

install.packages("midfielddata",
  repos = "https://MIDFIELDR.github.io/drat/",
  type = "source"
)

Usage

Data tables can be loaded individually or collectively as needed.

library(midfielddata)

# Load one table as needed
data(student)

# Or load multiple tables
data(course, term, degree)

Tutorials:

  • We examine these data in greater detail in the package articles.
  • How one uses these data is developed in detail on the midfieldr website.

Acknowledgments

The development of midfieldr and midfielddata was supported by the US National Science Foundation through grant numbers 1545667 and 2142087.

References

Barrett, Tyson, Matt Dowle, Arun Srinivasan, et al. 2026. data.table: Extension of data.frame. R package version 1.18.4. https://CRAN.R-project.org/package=data.table.
Layton, Richard, Russell Long, Susan Lord, Matthew Ohland, and Marisa Orr. 2026. midfieldr: Tools and Methods for Working with MIDFIELD Data in R. R package version 1.0.0. https://github.com/MIDFIELDR/midfieldr.
Ohland, Matthew W., and Russell A. Long. 2016. “The Multiple-Institution Database for Investigating Engineering Longitudinal Development: An Experiential Case Study of Data Sharing and Reuse.” Advances in Engineering Education 5 (2). https://advances.asee.org/wp-content/uploads/vol05/issue02/Papers/AEE-18-Ohland.pdf.