  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.
