Assessment Dropped Item Weight Gap Tool

Description

Summarize retained weighted assessment points and removed item weight under a supplied drop mask.

Scoring rules combine points, item weights, boundaries and policies for omission, extra credit or missing items. A computed mark is meaningful only under those explicit rules; applying a rule does not establish its fairness or official status.

Summarize retained weighted assessment points and removed item weight under a supplied drop mask.

When to use this tool

Use Assessment Dropped Item Weight Gap when checking one supplied scoring contribution or policy boundary.

How to use the tool and how it works

Enter earned, maximum, weights, dropped. Keep parallel arrays aligned. Use the units and conventions below.
Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
Read earnedWeighted, possibleWeighted, removedWeight. Use the output convention below.

Require equally long earned, maximum, weights and dropped arrays, nonnegative weights and 0 <= earned[i] <= maximum[i]. Sum earned*weight and maximum*weight only for retained items; removedWeight sums dropped weights.^[1]

Input field	Meaning and units	Accepted input
earned	Earned	Required. Array of finite number; maximum items 256.
maximum	Maximum	Required. Array of finite number; maximum items 256.
weights	Position-aligned nonnegative weights under the specified model convention.	Required. Array of finite number; maximum items 256.
dropped	Dropped	Required. Array of boolean; maximum items 256.

Output field	Interpretation	Returned shape
earnedWeighted	Earned Weighted	Required. Finite number.
possibleWeighted	Possible Weighted	Required. Finite number.
removedWeight	Removed Weight	Required. Finite number.

json

{
  "input": {
    "earned": [
      8,
      5
    ],
    "maximum": [
      10,
      10
    ],
    "weights": [
      1,
      2
    ],
    "dropped": [
      false,
      true
    ]
  },
  "output": {
    "earnedWeighted": 8,
    "possibleWeighted": 10,
    "removedWeight": 2
  }
}

Limitations and assumptions

No final ratio is computed, so a zero retained maximum remains visible without an implied grade. Dropping policy, score scaling and weight normalization are supplied.
Inputs must satisfy both the field types and the cross-field conditions above. Invalid input causes an error; a successful false flag or documented placeholder is a different result.
Numeric calculations use binary floating point unless exact decimal-integer arithmetic is explicitly stated. No hidden measurement tolerance or decimal rounding is added; nonfinite or out-of-contract results are rejected. Numeric signed-zero results are exported as zero.

Alternative or Complementary methods

Use the complete approved rubric and score record for an official outcome, and examine measurement quality separately.

References

Calculation and input contract: education/assessment-dropped-item-weight-gap — tool.io

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