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Bloom’s Revised Taxonomy

SyllabusApplication of AI in education

Social IssuesPublished 25 September 2026

Bloom's revised taxonomy is a framework for arranging learning objectives according to increasing cognitive complexity. Revised in 2001 from Bloom's original taxonomy, it classifies cognitive processes as Remember, Understand, Apply, Analyze, Evaluate and Create.

Levels of cognitive learning

The categories move from retrieving existing knowledge towards independently judging and producing knowledge. The progression is broadly from lower-order thinking to higher-order thinking.

  • Remember means retrieving relevant facts, terms or ideas from long-term memory.
  • Understand means explaining, interpreting, classifying, summarising or comparing meaning.
  • Apply means using a learned procedure or principle in a given situation.
  • Analyze means separating material into parts and identifying their relationships, organisation or purpose.
  • Evaluate means making judgments according to stated criteria or standards.
  • Create means combining elements into a coherent whole, new pattern or original product.

What the revision changed

The revision expresses cognitive processes as action-oriented verbs. It places Create above Evaluate, unlike the original taxonomy, in which synthesis preceded evaluation.

  • The revised framework also identifies four knowledge types: factual, conceptual, procedural and metacognitive knowledge.
  • Learning objectives can be located by combining a knowledge type with a cognitive process, such as applying procedural knowledge or evaluating conceptual knowledge.

Use in education and AI-enabled learning

Teachers can use the taxonomy to align learning objectives, classroom activities and assessment. In AI-enabled education, it helps distinguish tools that merely support recall and comprehension from those that scaffold application, analysis, evaluation and creation.

  • Assessment should test the intended cognitive process rather than treat fluent reproduction of information as evidence of higher-order learning.
  • AI activities can progress from personalised explanation and practice to problem-solving, critical appraisal and guided creation.

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