Bloom Taxonomy Verb Wheel Level Classifier

Exact verb in caller context-specific Bloom crosswalk with multiple levels retained; verbal one cannot determine cognitive demand, unmatched returns no evidence. Caller independently verifies learner/context/evidence and reference edition; not causal learning efficacy, disability eligibility or educational certification.

Description

A task’s cognitive demand depends on more than its verb.

A task’s cognitive demand depends on more than its verb.^[1]

This crosswalk preserves every matched Bloom level supplied for an exact verb and leaves an unmatched verb unclassified.

When to use Bloom Taxonomy Verb Wheel Level Classifier

Use this tool to calculate or review the supplied observations under the stated rules. Establish the learning task, observed evidence and applicable framework or policy edition.

How to use Bloom Taxonomy Verb Wheel Level Classifier and understand its results

Establish the learning task, observed evidence and applicable framework or policy edition.
Enter observedInstructionVerb, callerContextVerbKeys, callerContextBloomLevels, using the field meanings and rules below, then run the tool.
Read compatibleCallerBloomLevels. Inspect nested result fields where present, and review unknown records separately from known matches.
Correct any reported input issue and run again. Before using a successful result, check the stated units, signs, reference scope and observation coverage.

Input field	Meaning	Value type	Requirement
observedInstructionVerb	Observed instruction verb	string	Required
callerContextVerbKeys	Caller context verb keys	list of string	Required
callerContextBloomLevels	Caller context bloom levels	list of string	Required

Enter nonempty aligned verb keys and supported level tokens remember, understand, apply, analyze, evaluate or create. Verb keys may repeat. Match the query exactly and return distinct matching levels in first-occurrence order; no match returns an empty list.

levels=distinctInOrder(level_i where verb_i=query)

Use the matching field units and the exact boundary, ordering and reference rules above.

Output field	Meaning	Value type
compatibleCallerBloomLevels	Compatible caller bloom levels	list of string

json

{
  "input": {
    "observedInstructionVerb": "explain",
    "callerContextVerbKeys": [
      "explain",
      "explain",
      "list"
    ],
    "callerContextBloomLevels": [
      "understand",
      "analyze",
      "remember"
    ]
  },
  "output": {
    "compatibleCallerBloomLevels": [
      "understand",
      "analyze"
    ]
  }
}

Limitations and assumptions

Supplied annotations and framework choices determine the result. The tool does not measure learning effects, assess learner intent or independently establish policy applicability.

Missing required fields, unknown fields, wrong types and violated rules return input issues. Numeric values and outputs must be finite. Lists and matrices must be dense, without missing cells. Numeric lists allow at most 10000 entries; ordinary string lists allow at most 128 strings of 128 UTF-16 units each; numeric matrices allow at most 128 rows and 128 columns, subject to narrower requirements above.

Alternative or Complementary methods

For a related step, use Higher Order HOTS Question Stems By Bloom Level Bank: Higher-order question stems need to be matched to the task and intended thinking rather than a verb alone. For a complementary comparison, use Solo Taxonomy Prestructural Extended Abstract Levels Lookup: SOLO describes the structure and complexity of a learning response.

References

Bloom Taxonomy Verb Wheel Level Classifier — tool.io

Similar or alternative tools

Higher Order HOTS Question Stems By Bloom Level Bank
Higher-order question stems need to be matched to the task and intended thinking rather than a verb alone.
Solo Taxonomy Prestructural Extended Abstract Levels Lookup
SOLO describes the structure and complexity of a learning response.