“We implemented a model for grading weekly assignments in an intermediate data science course that explicitly gave students useful feedback on their code while not evaluating it on the traditional metrics of correctness or style. … Our ungrading policy was designed to extend empathy towards students and to give them useful, actionable feedback. Our policy reduced the stress that students felt each week, stabilized the amount of time they spent on assignments, and ask them to reflect on their code to request feedback from the teaching team.”

Find the paper and the full list of authors in the SIGCSE 2023 proceedings.