{"id":779,"date":"2025-08-31T23:47:23","date_gmt":"2025-08-31T23:47:23","guid":{"rendered":"http:\/\/www.nilbar.com\/?p=779"},"modified":"2025-09-01T10:33:19","modified_gmt":"2025-09-01T10:33:19","slug":"using-the-revised-blooms-taxonomy-to-enhance-ai-literacy","status":"publish","type":"post","link":"http:\/\/www.nilbar.com\/index.php\/2025\/08\/31\/using-the-revised-blooms-taxonomy-to-enhance-ai-literacy\/","title":{"rendered":"Using the Revised Bloom\u2019s Taxonomy to Enhance AI Literacy"},"content":{"rendered":"
Bloom\u2019s 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.<\/p>\n
If anything, Bloom\u2019s 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.<\/p>\n
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\u2019s Revised Taxonomy can be paired with AI to enhance learning.<\/p>\n