Measuring the real value of higher education
Higher education is one of the most consequential financial decisions a person makes. ROEDU is designed to make that decision measurable, comparable, and grounded in data — not guesswork.
ROEDU(Return on Education) is a data-driven framework that estimates the economic return of an education choice by comparing the cost of earning a credential with the financial outcomes it produces. It answers a simple, practical question:
If I invest in this education, what do I get back — and how long does it take?
Unlike rankings or reputation, ROEDU focuses on value: cost, earnings potential, time, and risk. All combined into a single score you can use to compare options.
Most students make decisions based on:
These signals don’t measure return. Two students can pay the same tuition and have very different outcomes depending on major, program length, debt, and labor market conditions. ROEDU brings visibility to those differences before decisions are made.
ROEDU condenses complex data into a single score:
| Score Range | Interpretation |
| 900-999 | Exceptional Return |
| 800-899 | Strong Return |
| 700-799 | Above Average Return |
| 600-699 | Moderate Return |
| 500-599 | Marginal Return |
| <500 | Higher Risk / Lower Return |
Higher scores indicate stronger estimated returns relative to cost.
ROEDU turns complex data into practical insights you can use at every stage of planning:
It gives you a consistent frame of reference, no matter your goals or circumstances.
Explore how ROEDU applies across schools, majors, programs, and pathways.
Built on real-world education and outcome data. Learn what data goes into ROEDU, how it’s sourced, and how we ensure relevance and reliability.
From score to strategy: using ROEDU in real decisions.
What drives higher return on education. Explore the factors that consistently increase value (Ex. Field demand, cost efficiency, time to payoff, etc.).
Clear expectations build trust. Understand what ROEDU measures, what it doesn’t, and how to use it responsibly.
Designed for transparency, not hype. A deeper look at assumptions, tradeoffs, and the limits of what data can and can’t predict.