Statistical personas identify unfair reviewers in peer grading systems.
We developed a data validation process to ensure fairness in peer reviews. The process analyzes metrics like total review time, time spent on each review, and number of comments left on each project. Most variables followed a Gaussian distribution, letting us use statistical tools to identify problematic reviewers. We built student personas including Lazy Graders, Harsh and Happy Graders, and Misaligned Students. Examining just three to four projects from a single student typically gave us enough insight to determine if they fit these personas, and we would re-evaluate their feedback accordingly.