Economic Behavior of Information Acquisition: Impact on Peer Grading in Massive Open Online Courses.

The article investigates the economic behavior of student graders in massive open online courses (MOOCs) and its impact on the accuracy and bias of peer grading systems. It models grading as a costly information acquisition and reporting process, showing that student graders strategically balance these costs and benefits, leading to a systematic bias of grades toward the mean and reduced learning effort. The study identifies a unique equilibrium in graders' information acquisition and reporting strategies, demonstrating that strategic reporting exacerbates grading inaccuracies and bias. To address these issues, the authors propose a scale-shift grading scheme—a linear transformation of the average peer grades—that can improve grading accuracy, reduce bias, and incentivize truthful reporting and greater student learning. They discuss practical implementation challenges and provide simulation evidence supporting the scheme's effectiveness in enhancing peer grading outcomes in MOOCs.