Score normalization

In Smart Assessment Engine normalization maps the actual scores to a standardized scale, typically from 0 through 100, enabling for a unified evaluation framework.

Normalization approach overview

In Smart Assessment Engine normalization adjusts individual assessment scores to a common scale, enabling comparison across different assessments. Normalization of assessment scores can be achieved through two approaches: Maximizing values, where higher scores are desirable, and minimizing values, where lower scores are preferred.

To maximize the value	Maximize the value when higher values are better. The following formula is used to get the normalized score: Normalized Score (High) = ((raw score - minimum Score) / (maximum score - minimum score)) * (scale factor maximum - scale factor minimum) + scale factor minimum
To minimize the value	Minimize the value when lower values are better. The following formula is used to get the normalized score: Normalized Score (High) = (1 - (raw score - minimum Score) / (maximum score - minimum score)) * (scale factor maximum - scale factor minimum) + scale factor minimum

Where,

• Raw score = Actual score calculated
• Minimum score = The minimum value of the current scale.
• Maximum score = The maximum value of the current scale.
• Scale factor maximum = The minimum value of the target scale.
• Scale factor minimum = The maximum value of the target scale.
• Scale definition = Specifies the scoring direction: 'high' for higher scores being better or 'low' for lower scores being better.
• Relative Scaling = When enabled the normalized score is calculated relative to the maximum value.

Note:

This approach is applicable only when the linear normalization strategy is used. The formulas may vary if a different strategy is selected.