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Linear Rescaling
“The Honest Reset”
Everyone gets the same points added (e.g. +10 across the board). The lowest score rises to match your minimum acceptable threshold.
curved = score + adjustment Best for: Most exams The scenario
- The test was harder than expected; the highest score was 78%.
- You set 70% as the minimum passing threshold for mastery.
- Adding 10 points brings the highest to 88% and the lowest to at least 60%+.
How to justify it
- You are not curving the class — you are adjusting the scale because the test difficulty was miscalibrated.
- Everyone benefits equally; there is no favoritism.
- You are protecting legitimate mastery — students who studied still rank higher.
Data to show your administrator
- A before/after distribution (two columns: before scores vs. after).
- The passing-rate shift, e.g. "Before: 35% pass. After: 67% pass."
- That the top scorer still ranks first: a 78% becomes 88%, still ahead of everyone else.
When to use this justification
- The test was genuinely harder than your other assessments.
- You have no outlier students — everyone moves up the same amount.
- The administrator values simplicity and transparency.
Likely pushback — and how to answer it
- “Aren’t you just giving away points?”
- No — you are correcting for an assessment-design error, not rewarding low effort.
Tone to strike
Transparent, no-nonsense — "I adjusted the scale because…"
Try the Linear Rescaling curve →
Frequently Asked Questions
Why is linear curving called "linear"?
Because it adds a constant amount to every score, producing a straight-line shift. Graphed before and after, the two lines are parallel — a uniform adjustment.
What's the advantage of linear curving over other methods?
Simplicity. It’s the easiest to implement, explain, and verify. Students understand it immediately: "everyone gets X points." No formulas or statistics.
How do I implement linear curving in an LMS?
Most LMS don’t support bulk adjustments directly. Export grades to Excel, add a column of Original + X, then import back or update manually.
Can I apply different linear adjustments to different students?
You can, but you shouldn’t — that’s selective curving and is unfair. A curve should apply uniformly. For specific students, use a bonus assignment instead.
Is there a standard rule for how many points to add?
No universal rule. Common approaches: add enough so the top score hits 100%, add a fixed amount, or raise the lowest passing score to the threshold.
What if adding points shifts my grade boundaries?
That’s normal — adjust the boundaries accordingly and stay consistent with your syllabus.
Can I use linear curving per assignment or only on overall grades?
Both. Curve an individual assignment or the final grade — just be consistent.
How do I communicate linear curving to students?
Be direct and show an example: "The exam was harder than expected, so I’m adding X points to everyone’s score. Here’s how it affects your grade."
Does linear curving maintain ranking order?
Yes. Students keep their relative positions, assuming scores cap below 100%. Curving doesn’t reorder students.
What's the difference between linear curving and a bonus assignment?
Linear curving adjusts historical grades; a bonus assignment lets students earn points going forward. Use curving for past assessments and bonuses for forward-looking adjustments.
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