Behind the Ratings: Investigating Biases in the Student Evaluation on Rate My Professor

This project investigates the systemic biases embedded in student evaluations on Rate My Professors (RMP) and their impact on perceptions of teaching quality. Millions of students use RMP to choose courses, but do these ratings truly reflect teaching effectiveness? Our research highlights how biases such as grading leniency, sampling bias, and review extremity bias distort professor evaluations, resulting in misleading assessments.

Using a dataset of 20,000 reviews from over 1,400 professors across 500 universities, we applied quantitative analysis and statistical methods to uncover patterns and correlations. We found that:

Professors labeled as “Tough Graders” received significantly lower ratings regardless of teaching quality (Grading Leniency Bias).

75% of professors had 41 or fewer reviews, indicating that a small percentage of highly-reviewed professors dominate student perceptions (Sampling Bias).

Professors with fewer displayed the highest variability, leading to more extreme ratings (Review Extremity Bias).

Our findings have important implications: students may be misled into avoiding effective professors, while strict or experienced educators suffer reputational harm. To address these issues, we propose solutions such as integrating university evaluations, implementing mandatory RMP reviews, introducing weighted rating systems, and launching student awareness campaigns to promote fair and constructive feedback.

Through this research, we aim to raise awareness of biases in online teaching evaluations and propose actionable solutions for a more transparent and reliable student feedback system.