Webpage for the University of Chicago Data Science Clinic
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This page contains all grading rubrics used in the Data Science Clinic. These rubrics help ensure consistent evaluation across projects and provide clear expectations for deliverables.
Used to evaluate the GitHub issues each student opens after the mentor session describing their tasks for the coming week. Covers task descriptions, acceptance criteria, and timeliness. Students are graded against the weekly tasks template.
Used to evaluate the weekly report each student posts as a comment on last week’s issues, along with the code they pushed to GitHub. Assesses progress made, accuracy of reported statuses, and how blockers were handled. Students are graded against the weekly report template.
Used to evaluate team presentations given during Week 6 of each quarter. Covers presentation quality, technical content, and team collaboration.
Used to evaluate the one-page project summaries that teams create for external distribution. Focuses on clarity, technical accuracy, and audience appropriateness.
Used to evaluate team member contributions and effort throughout the quarter. Peer reviews are conducted at weeks 3, 6, and 10, providing feedback on workload distribution, professionalism, and team collaboration.
Used to evaluate the final project video that teams create for client presentation. Covers technical content, presentation quality, and storytelling.
Used to evaluate the final project summary email that teams send to clients. Assesses communication clarity, technical accuracy, and professional presentation.
Used to evaluate the technical documentation and code organization that teams provide at project completion. Covers code quality, documentation, and reproducibility.