Automated grading workflows for providing personalized feedback to open-ended data science assignments

TL;DR

This paper introduces gradetools, an R package that automates parts of the grading process for open-ended data science assignments, enabling efficient, consistent, and personalized feedback for students.

Contribution

It presents a new automated grading workflow and an R package that streamlines grading and feedback for open-ended assignments in data science education.

Findings

Facilitates efficient grading workflows

Enables consistent and personalized feedback

Integrates seamlessly with RStudio

Abstract

Open-ended assignments - such as lab reports and semester-long projects - provide data science and statistics students with opportunities for developing communication, critical thinking, and creativity skills. However, providing grades and formative feedback to open-ended assignments can be very time consuming and difficult to do consistently across students. In this paper, we discuss the steps of a typical grading workflow and highlight which steps can be automated in an approach that we call automated grading workflow. We illustrate how gradetools, a new R package, implements this approach within RStudio to facilitate efficient and consistent grading while providing individualized feedback. By outlining the motivations behind the development of this package and the considerations underlying its design, we hope this article will provide data science and statistics educators with ideas for improving their grading workflows, possibly developing new grading tools or considering use gradetools as their grading workflow assistant.