When defining response outcomes, you have the ability to define tolerance levels for the deviation of results. This feature allows you to author more comprehensive questions while ensuring that candidates are not penalized for small deviations that still demonstrate their understanding.

To maintain compatibility with the QTI (Question and Test Interoperability) standard for storing content and enabling the use of these questions in other systems, we utilize the formulas defined by the standard for evaluating tolerance levels (found below).

Content

• Absolute tolerance
  • Example
• Relative tolerance
  • Example 1
  • Example 2

Absolute tolerance

Absolute tolerance is used when you want to define a response outcome that falls within an absolute lower and upper bound of a variable. For a candidate response to meet the response outcome, it should be within the range of variable minus lower bound, variable plus upper bound, where lower and upper bounds are numbers.

Example

Question:

How high is Mount Everest?

Instructions:

The correct answer to be 8848 (meters) and want to allow +/- 10 meters to allow for fluctuations in snow levels.

Adding 10 as both lower and upper bounds, and setting the response outcome as CORRECT, any answer within the range of 8838 - 8858 will be CORRECT.

Relative tolerance

Relative tolerance allows you to define a response outcome that falls within a specified percentage range of a variable, rather than requiring an exact match. The acceptable range is determined by variable minus (lower bound% * variable) and variable plus (upper bound% * variable), with both the lower and upper bound as numbers.

Note: When using negative values and calculating relative tolerance, it is important to verify the desired outcome by plugging the numbers into the provided formula.

Example

Question:

What is the population of Switzerland?

Instructions:

The right answer is around 8.7 million. Due to fluctuations, we want to allow for a lower bound of 1% deviation and upper bound of 5% deviation.

Adding 1% as lower bound and 5% as upper bound, and setting the response outcome as CORRECT, any answer within the range 8.613 million - 9.135 million will as CORRECT.