See also Examples of Bloom’s Taxonomy in the Classroom
Bloom’s Digital Taxonomy: Understanding & Evaluating Digital Tasks
by TeachThought Staff
What Is Bloom’s Digital Taxonomy? (Framework & Evaluation)
At TeachThought, we describe Bloom’s Taxonomy as “a hierarchical ordering of cognitive skills that, among countless other uses, helps teachers teach and students learn.”
Whether you’re designing instruction, evaluating an assessment, or observing a classroom, Bloom’s remains a practical lens for understanding how thinking happens—and how to support it through intentional lesson design.
Bloom’s Digital Taxonomy aligns the classic cognitive levels—Remember, Understand, Apply, Analyze, Evaluate, Create—with contemporary digital actions so that technology serves thinking, not the other way around. The framework is tool-agnostic and evolves as platforms change; the constant is cognitive demand.
Using the Framework to Evaluate Digital Tasks
When planning or reviewing tech-rich work, start from cognition and make thinking visible. Use criteria and artifacts that match the level, and evaluate both process and product.
- Define evidence of thinking: What artifact, reflection, or performance shows the intended level?
- Separate novelty from rigor: New tools ≠ higher-order thinking; align tasks to level-appropriate criteria.
- Interaction quality: Move beyond posting to purposeful collaboration—feedback, critique, iteration, and revision.
- Source quality & attribution: Require cite-checking and transparent use of AI or automation.
Evaluation Checklist (Using the Framework)
- Intent: Which cognitive level is targeted (Remember → Create)? Is it explicit to students?
- Evidence: What products or performances will make the thinking visible?
- Criteria: Do rubrics match the level (e.g., analysis ≠ recall)?
- Scaffolds: Prompts, models, and exemplars support—but don’t replace—student thinking.
- Process: Iteration, feedback, and revision are built into the task flow.
- Source quality: Students verify claims and attribute media/AI assistance.
- Equity & access: Tools, time on task, and supports are equitably available.
The Communication Spectrum
In digital spaces, the quality of interaction matters. Move from simple posting and reacting toward purposeful collaboration—planning, critique, co-authoring, and revision that align with higher levels of Bloom’s.
AI Use, Citation, and Transparency
When AI is permitted, require documentation that makes cognition visible and verifiable:
- Prompt logs: Students submit prompts and key iterations (what changed and why).
- Cite-check: All claims and quotations are verified with citable sources; AI outputs aren’t sources.
- Attribution: Students note where AI contributed (idea generation, outline, polish) and where human judgment prevailed.
- Limitations & risks: Students describe model limitations, risks, and mitigations (e.g., red-teaming, alternate sources).
- Assessment fit: Rubrics include process, evidence quality, and ethical use—not just the final product.
Key Takeaway
Use Bloom’s Digital Taxonomy to make the thinking behind digital work explicit. Start with the cognitive goal, design tasks and supports accordingly, and assess both the product and the process—including transparent AI usage, citations, and reasoning.
Related Resources
Bloom, B. S., Engelhart, M. D., Furst, E. J., Hill, W. H., & Krathwohl, D. R. (1956). Taxonomy of Educational Objectives: The Classification of Educational Goals. Handbook I: Cognitive Domain. New York: David McKay Company.
Anderson, L. W., & Krathwohl, D. R. (Eds.). (2001). A Taxonomy for Learning, Teaching, and Assessing: A Revision of Bloom’s Taxonomy of Educational Objectives. New York: Longman.
Churches, A. (2009). Bloom’s Digital Taxonomy. (Widely circulated adaptations emphasize aligning technology tasks to cognitive levels rather than specific tools.)