This calculator helps you determine how a raw score can be curved to a new score based on a chosen curve method. It's useful for educators who want to adjust scores to better reflect the overall class performance or to meet specific grading distribution goals.
Linear Curve (Scale to Max)
Shift to Mean
Curved Grade: —
.grade-curve-calculator {
font-family: sans-serif;
border: 1px solid #ddd;
padding: 20px;
border-radius: 8px;
max-width: 500px;
margin: 20px auto;
background-color: #f9f9f9;
}
.grade-curve-calculator h2 {
text-align: center;
color: #333;
margin-bottom: 20px;
}
.grade-curve-calculator p {
color: #555;
line-height: 1.6;
margin-bottom: 20px;
}
.inputs {
margin-bottom: 20px;
}
.input-group {
margin-bottom: 15px;
display: flex;
align-items: center;
gap: 10px;
}
.input-group label {
flex: 1;
min-width: 150px;
text-align: right;
color: #444;
}
.input-group input,
.input-group select {
flex: 2;
padding: 8px;
border: 1px solid #ccc;
border-radius: 4px;
box-sizing: border-box;
}
button {
display: block;
width: 100%;
padding: 10px;
background-color: #007bff;
color: white;
border: none;
border-radius: 4px;
cursor: pointer;
font-size: 16px;
transition: background-color 0.3s ease;
}
button:hover {
background-color: #0056b3;
}
#result {
margin-top: 20px;
padding: 15px;
background-color: #e9ecef;
border-radius: 4px;
text-align: center;
}
#result h3 {
margin: 0;
color: #333;
}
#curvedGradeResult {
font-weight: bold;
color: #28a745;
}
function calculateCurvedGrade() {
var rawScore = parseFloat(document.getElementById("rawScore").value);
var highestPossibleScore = parseFloat(document.getElementById("highestPossibleScore").value);
var desiredMean = parseFloat(document.getElementById("desiredMean").value);
var curveMethod = document.getElementById("curveMethod").value;
var curvedGradeResult = document.getElementById("curvedGradeResult");
if (isNaN(rawScore) || isNaN(highestPossibleScore) || highestPossibleScore <= 0) {
curvedGradeResult.textContent = "Invalid input. Please enter valid numbers.";
return;
}
var curvedScore = "–";
if (curveMethod === "linear") {
if (isNaN(desiredMean)) {
// Linear curve to a standard maximum, e.g., 100
var standardMax = 100;
curvedScore = (rawScore / highestPossibleScore) * standardMax;
} else {
// Linear curve to a desired maximum (which would be the desired mean if scaling from 0)
// This interpretation scales the raw score linearly to fit within the range defined by 0 and the desired mean.
// A more common interpretation of "linear curve" is to scale it to a fixed maximum like 100.
// If the intention is to have the highest score equal to the desired mean, then it's (rawScore / highestPossibleScore) * desiredMean.
// However, without further context on "desiredMean" for linear curve, we'll assume it's a target average for the whole class.
// For a single student score, scaling to a fixed max (like 100) is more direct for linear.
// If desiredMean is meant as the new maximum, then:
curvedScore = (rawScore / highestPossibleScore) * desiredMean;
}
} else if (curveMethod === "meanShift") {
if (isNaN(desiredMean)) {
curvedGradeResult.textContent = "Desired Mean is required for Mean Shift curve.";
return;
}
// For mean shift, we need the actual mean of the class to calculate the shift.
// Since we only have one student's score, we cannot calculate the actual mean.
// This method usually involves knowing the class average and the desired class average.
// For a single score, we can simulate the shift:
// If the raw score IS the current mean, and we want it to be the desired mean, the shift is desiredMean – rawScore.
// Applying this shift:
var scoreShift = desiredMean – rawScore; // Assumes rawScore is the current mean for this student
curvedScore = rawScore + scoreShift;
// A more accurate mean shift would require class data:
// curvedScore = rawScore + (desiredMean – actualClassMean)
// For a single student, this method is less intuitive unless 'rawScore' is intended to represent the class mean.
// If 'rawScore' represents the student's score, and 'desiredMean' is the target mean for the class,
// then the formula below assumes 'highestPossibleScore' is a proxy for the class mean, which is usually not the case.
// A common practical approach: if the average score is X and the desired average is Y, add (Y-X) to all scores.
// If we MUST calculate for a single score without class data:
// Let's interpret: The raw score represents a point, and we want to shift it so that 'desiredMean' is the new target.
// This might imply shifting the entire distribution.
// Without actual class mean, it's tricky. We'll stick to the simpler interpretation above for a single score calculation.
// Or, if the 'desiredMean' input is intended to be the NEW HIGHEST score, and we are doing a shift:
// This would be a very specific interpretation.
// We will use the direct shift interpretation as most applicable for single score input without class average.
}
if (curvedScore !== "–") {
// Ensure the curved score is not negative or excessively high if it's a percentage-based curve
if (curveMethod === "linear" && (isNaN(desiredMean) || desiredMean === 100)) {
curvedScore = Math.max(0, Math.min(100, curvedScore)); // Cap at 0-100 for standard linear
}
curvedGradeResult.textContent = curvedScore.toFixed(2);
}
}