Using the Revised Bloom’s Taxonomy to Enhance AI Literacy

Bloom’s Revised Taxonomy provides an important framework for integrating, assessing, and evaluating the role of AI in your instruction. While the taxonomy has its limitations (like any model) it remains a powerful lens for helping educators design lessons that move students beyond surface learning and into deeper levels of understanding and creativity.

If anything, Bloom’s framework highlights the fact that learning is not a flat process. It is an iterative, dynamic, interactive, and on-going process. Students need opportunities to remember and understand concepts, for sure, but they also need structured chances to apply knowledge, analyze information, evaluate claims, and ultimately create something new.

These stages translate beautifully into the age of AI, where tools like ChatGPT, Claude, Gemini, Canva AI, or Quizlet AI can support both teachers and learners when used intentionally. In this guide, I broke down how each level of Bloom’s Revised Taxonomy can be paired with AI to enhance learning.

Related: Systems Thinking Guide for Teachers

The Original Bloom’s Taxonomy

The original Bloom’s Taxonomy, published in 1956, was designed as a framework for classifying educational objectives. Benjamin Bloom and his colleagues created it to give educators a common language for describing learning goals and to help align teaching, assessment, and curriculum.

The taxonomy organized cognitive skills into six hierarchical levels: Knowledge, Comprehension, Application, Analysis, Synthesis, and Evaluation, moving from simple recall of facts to more complex and abstract thinking. The taxonomy quickly became a cornerstone in teacher education, widely used to design test items, plan lessons, and ensure that students were being challenged at different levels of thinking.

Over time, however, critiques of the original taxonomy emerged. One limitation was its heavy focus on rote recall: analyses of curricula and tests often revealed an overemphasis on the Knowledge category, with far fewer objectives requiring higher-order thinking. Another issue was that the “Knowledge” category was conceptually inconsistent, since it mixed content (what students should know) with cognitive processes (what students should do with that knowledge).

Critics also argued that the hierarchy was too rigid, implying that one had to master each lower level before moving up, even though in practice these levels often overlap. Finally, the taxonomy’s language was sometimes out of sync with how teachers naturally described learning goals.

The Revised Bloom’s Taxonomy

The Revised Bloom’s Taxonomy, published in 2001 by Anderson and Krathwohl, addressed many of these concerns. It restructured the framework into two dimensions: a Knowledge Dimension (factual, conceptual, procedural, and metacognitive knowledge) and a Cognitive Process Dimension (remember, understand, apply, analyze, evaluate, create).

The categories were reframed as verbs to reflect active thinking, and “Synthesis” was renamed and repositioned as “Create,” now considered the highest and most complex form of thinking. This two-dimensional approach allowed educators to classify objectives, activities, and assessments more precisely, providing a tool not just for measurement but also for curriculum alignment, instructional planning, and encouraging deeper forms of learning.

Pairing the Revised Bloom’s Taxonomy with AI

Create

Here are general Create level activities:

• Create a lesson plan for teaching a concept to younger students
• Design an assessment that measures student understanding in a new way
• Develop a unit plan connecting multiple subjects around one theme
• Generate original problems or scenarios for students to solve
• Construct a rubric for evaluating student projects
• Plan a field trip experience with pre- and post-activities
• Produce instructional materials (videos, infographics, guides) for a topic
• Design a classroom management system for specific student needs
• Create a parent communication strategy for your subject area
• Develop intervention activities for struggling learners

AI tools to use for this level: ChatGPT, Claude, Canva AI, Gemini, Poe, Gamma

Evaluate

Here are Evaluate level activities where AI can help:

• Have AI provide criteria and frameworks for students to judge the quality of sources or arguments
• Ask AI to model how to critique creative work, research papers, or problem solutions
• Use AI to help students assess the strengths and weaknesses of different approaches or strategies
• Have AI demonstrate how to defend a position using evidence and logical reasoning
• Ask AI to show students how to justify their choices or conclusions with supporting details
• Use AI to help students appraise the credibility and bias of news articles or websites
• Have AI model peer review processes by critiquing sample student work
• Ask AI to help students judge the effectiveness of different solutions to real-world problems
• Use AI to demonstrate how to assess whether evidence supports or contradicts a claim
• Have AI show students how to critique experimental design or research methodology
• Ask AI to help students defend their interpretations of literature or historical events
• Use AI to model how to appraise the ethical implications of decisions or policies

AI tools to use for this level: ChatGPT, Claude, Scite AI, Gemini, Consensus, Eduaide

Related: AI Literacy and Data Literacy: Skills Every Teacher Needs

Analyze

Here are Analyze level activities where AI can help:

• Use AI to break down complex texts into main ideas, supporting details, and underlying themes
• Have AI compare and contrast different historical perspectives on the same event
• Ask AI to organize student assessment data by learning standards and identify patterns
• Use AI to differentiate between fact and opinion in news articles or primary sources
• Have AI deconstruct writing samples to identify rhetorical strategies and techniques
• Ask AI to analyze student work samples and categorize common errors or misconceptions
• Use AI to compare curriculum standards across different grade levels or states
• Have AI organize research sources by credibility, bias, and relevance to your topic
• Ask AI to attribute quotes, ideas, or artistic techniques to their original sources
• Use AI to analyze classroom discussion transcripts and identify participation patterns
• Have AI contrast different problem-solving approaches in math or science
• Ask AI to differentiate between various learning styles represented in student responses

AI tools to use for this level: ChatGPT, Claude, Elicit, Perplexity, Scholarcy, Gemini

Apply

Here are Apply level activities where AI can help:

• Use AI to generate practice problems that implement specific mathematical concepts
• Have AI demonstrate step-by-step solutions to science experiments or math procedures
• Ask AI to solve sample problems using the same method you taught in class
• Use AI to implement grammar rules by generating correct and incorrect sentence examples
• Have AI perform calculations or execute scientific formulas with real-world data
• Ask AI to demonstrate how historical events apply to current situations
• Use AI to execute writing techniques by creating examples in different styles or genres
• Have AI implement classroom procedures by walking through scenarios step-by-step
• Ask AI to solve word problems using specific strategies you’ve taught
• Use AI to perform language translations and explain the application of grammar rules
• Have AI demonstrate lab safety procedures through detailed scenario walkthroughs
• Ask AI to execute research methods by showing how to apply them to new topics

AI tools to use for this level: ChatGPT, Claude, MagicSchool, Gemini, Photomath, Gamma

Understand

Here are Understand level activities where AI can help:

• Have AI summarize complex readings or research articles in student-friendly language
• Ask AI to explain difficult concepts using analogies or metaphors students can relate to
• Use AI to interpret data sets, graphs, or charts and explain what they show
• Have AI classify vocabulary words, historical events, or scientific phenomena into categories
• Ask AI to compare different theories, characters, or historical periods side-by-side
• Use AI to exemplify abstract concepts with concrete, relatable examples
• Have AI paraphrase complex instructions or academic texts for different reading levels
• Ask AI to explain the same concept multiple ways for different learning preferences
• Use AI to interpret primary source documents and explain their historical context
• Have AI summarize video content or lectures for review purposes
• Ask AI to explain cause-and-effect relationships in science or social studies
• Use AI to classify student questions by difficulty level or learning objective

AI tools to use for this level: ChatGPT, NotebookLM, Gemini, Brisk Teaching, Otter AI, Elicit

Remember

Here are Remember level activities where AI can help:

• Have AI generate flashcards for key vocabulary terms, dates, or formulas
• Ask AI to create lists of important facts, names, or concepts for study guides
• Use AI to define technical terms or academic vocabulary in simple language
• Have AI quiz students on factual recall with multiple choice or fill-in-the-blank questions
• Ask AI to identify key elements, characters, or components in texts or images
• Use AI to create memory aids like mnemonics or acronyms for lists and sequences
• Have AI repeat important information in different formats (visual, auditory, written)
• Ask AI to generate practice exercises for recognizing patterns, symbols, or examples
• Use AI to create recall games or activities that reinforce basic facts
• Have AI list the steps in procedures or processes students need to memorize
• Ask AI to identify and highlight key information students should remember from readings
• Use AI to create repetition exercises that help cement foundational knowledge

AI tools to use for this level: Quizlet, QuizGPT, Study Mode, Kahoot, Quizizz, Khanmigo

Here is a downloadable guide to use in your teaching

References

• Anderson, L., & Krathwohl, D. A. (2001). Taxonomy for learning, teaching and assessing: A revision of Bloom’s Taxonomy of Educational Objectives. New York: Longman.
• AI for Education. (2025). Create a Bloom’s taxonomy with an AI chatbot. AI for Education. https://www.aiforeducation.io/prompts/blooms-taxonomy
• Berger, R. (2018, March 14). Here’s what’s wrong with Bloom’s taxonomy: A deeper learning perspective. Education Week, 1(3), 1–3. Retrieved August 31, 2025, from https://www.edweek.org/teaching-learning/opinion-heres-whats-wrong-with-blooms-taxonomy-a-deeper-learning-perspective/2018/03
• Bloom, B.S. (Ed.), Engelhart, M.D., Furst, E.J., Hill, W.H., & Krathwohl, D.R. (1956). Taxonomy of educational objectives: The classification of edu- cational goals. Handbook 1: Cognitive domain. New York: David McKay
• Centre for Teaching Excellence, University of Waterloo. (n.d.). Bloom’s taxonomy. University of Waterloo. https://uwaterloo.ca/centre-for-teaching-excellence/catalogs/tip-sheets/blooms-taxonomy
• Furst, E. J. (1981). Bloom’s Taxonomy of Educational Objectives for the Cognitive Domain: Philosophical and Educational Issues. Review of Educational Research, 51(4), 441–453. https://doi.org/10.2307/1170361
• Johnson, J. P. (1977). Integrating educational theory and history. The History Teacher, 10(3), 425–433. https://www.jstor.org/stable/491852
• Krathwohl, D. R. (2002). A revision of Bloom’s taxonomy: An overview. Theory Into Practice, 41(4), 212–218. https://www.jstor.org/stable/1477405
• Oregon State University Ecampus. (2025). Bloom’s taxonomy revisited. Oregon State University. https://ecampus.oregonstate.edu/faculty/artificial-intelligence-tools/blooms-taxonomy-revisited