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Learning Objective Reference Depth Tool

Count literal nonempty objective-reference components under an explicit separator.

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Description

depth is the number of resulting components.

Assessment records use item identifiers, branch labels, hierarchy references and deadline metadata. Literal matching and position counting preserve the supplied conventions without validating content, actual eligibility or semantic answer equivalence.

depth is the number of resulting components.

When to use this tool

Use Learning Objective Reference Depth when checking an explicit assessment-record or answer-token rule.

How to use the tool and how it works

  1. Enter reference, separator. Use the units and conventions below.
  2. Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
  3. Read depth. Use the output convention below.

Require nonempty separator and no empty component after splitting reference on that literal separator. depth is the number of resulting components.1

Input fieldMeaning and unitsAccepted input
referenceReferenceRequired. Text; maximum UTF-16 length 8192.
separatorSeparatorRequired. Text; maximum UTF-16 length 8192.
Output fieldInterpretationReturned shape
depthDepthRequired. Safe integer.
json
{
  "input": {
    "reference": "course.unit.objective",
    "separator": "."
  },
  "output": {
    "depth": 3
  }
}

Limitations and assumptions

  • Depth starts at one for a single nonempty component. This parses a supplied hierarchy label without validating an objective taxonomy or educational content.
  • 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.

Alternative or Complementary methods

Review the actual record structure and approved grading policy when identity, content or official outcomes matter.

References

  1. Calculation and input contract: education/learning-objective-reference-depth — tool.io

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