Grade Curve Calculator
Apply a linear shift, a scaling, a square-root curve or a normal distribution fit to a set of marks, and see exactly who moves grade before deciding whether to curve at all.
Last reviewed by the Radiatus Cloud team
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Curving fixes a broken assessment, not a weak cohort
If a paper turns out harder than intended, the marks measure the paper as much as the students, and adjusting them is defensible. If the cohort genuinely knows less, moving the boundaries hides that rather than addressing it. The distinction matters because the two look identical in the mark distribution: only knowledge of the paper, the teaching and previous cohorts separates them. Curving without deciding which case applies is the problem.
Norm referencing and criterion referencing answer different questions
Fitting marks to a fixed distribution, so that a set proportion receives each grade, measures students against each other. Criterion referencing measures against a standard, so a whole cohort can in principle pass or fail. Norm referencing guarantees a spread of grades whatever the standard, which is why it is used where places are limited and why it is inappropriate where the grade is supposed to certify a competence.
Different curves move different students
A flat addition helps everyone equally and pushes the top past the maximum. Scaling helps the strongest most in absolute terms. A square-root curve helps the weakest most and compresses the top, which is why it is popular and why it distorts the ranking least at the top and most in the middle. Seeing which students change grade under each is more informative than the method's name.
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Frequently Asked Questions
When is curving justified?
When the assessment turned out harder or easier than intended, so the marks measure the paper as much as the students. It is not justified as a way of hiding that a cohort learned less, and the mark distribution alone cannot distinguish the two.
What is the difference between norm and criterion referencing?
Norm referencing fits marks to a fixed distribution so a set proportion gets each grade, measuring students against each other. Criterion referencing measures against a standard, so an entire cohort can pass or fail.
Which curve should I use?
Look at who changes grade rather than at the name. A flat addition helps everyone equally, scaling helps the strongest most, and a square-root curve helps the weakest most while compressing the top.
Does curving ever lower marks?
Scaling and distribution fitting can, if the cohort scored above the target. Many institutions only permit upward adjustment, which turns curving into a one-way ratchet that inflates grades over time.
Should I tell students the marks were curved?
Yes. An unexplained adjustment undermines confidence in the marking, and students comparing raw and final marks will notice. Stating the reason and the method is straightforward when the reason is defensible.
Privacy & Security
Everything runs in your browser; nothing is uploaded.
How to Use
Paste your marks to see how each curving method changes them.
Disclaimer: This tool is provided "as is" without warranty of any kind. Results are for educational and utility purposes.