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AI Cognitive Framework
The New AI Cognitive Framework
Transform Learning for the AI Era
The New AI Cognitive Framework revolutionizes how we teach, learn, and create in the era of intelligent technologies. This model empowers educators and learners to critically curate, interpret, strategize, deconstruct, validate, and innovate skills essential for thriving in a world shaped by AI. Join the movement to future proof education and lead the next generation of thinkers and creators.
Cite as: Tariq, M. U. (2025). The New AI Cognitive Framework. The Case HQ. https://thecasehq.com/ai-cognitive-framework/
A Brief History of Learning Taxonomies
In 1956, Benjamin Bloom and his collaborators developed Bloom’s Taxonomy to classify educational objectives based on complexity and specificity. Originally, it organized learning into three domains: Cognitive (knowledge), Affective (emotions), and Psychomotor (skills).
The Cognitive Domain, which became the most influential, was structured into six levels:
Knowledge, Comprehension, Application, Analysis, Synthesis, Evaluation
In 2001, Anderson and Krathwohl revised the taxonomy, modernizing it by shifting from nouns to action verbs and slightly reordering the levels. The updated sequence is now widely adopted:
Remembering, Understanding, Applying, Analyzing, Evaluating, Creating
OUR FRAMEWORK
The Six Pillars of the New AI Cognitive Framework
The New AI Cognitive Framework equips learners and educators with the essential skills needed to thrive in an AI-driven world. Each level builds critical, ethical, and innovative capabilities for the future of education, research, and professional practice
Curate
Search, select, and organize information critically from AI and traditional sources to build reliable knowledge foundations
Interpret
Analyze and understand information through critical reflection, identifying biases and extracting deeper meaning
Strategize
Apply knowledge in ethical and strategic ways to solve real-world challenges using AI-enhanced insights
Deconstruct
Break down complex ideas, AI outputs, or arguments to examine structures, assumptions, and underlying logic
Validate
Critically evaluate the authenticity, originality, and ethical compliance of information and outputs
Innovate
Create original, human-centered solutions and research outcomes, leveraging AI responsibly and ethically
Example Action Verbs
GLOBAL MASTER ALIGNMENT TABLE
The New AI Cognitive Framework demonstrates robust international alignment with major qualifications frameworks including RQF (UK), SCQF (Scotland), AQF (Australia), QFEmirates (UAE), and QF-EHEA (Europe). Across all regions, cognitive development progresses consistently from early information curation at school levels through critical interpretation and strategic application at undergraduate levels, culminating in advanced deconstruction, validation, and innovation at postgraduate and doctoral stages. This coherence ensures the framework's adaptability to global education standards and future-oriented skill development.
Using Framework at School Level
In today's evolving world, preparing students for an AI-driven future must begin at school. The New AI Cognitive Framework provides a structured, progressive approach for developing the essential cognitive skills young learners need starting from the earliest levels of education. By adapting each cognitive stage to age-appropriate tasks, school teachers can cultivate critical thinking, ethical reasoning, and creative innovation from the very beginning. From basic exploration with AI in Pre-Nursery to critical validation and ethical innovation by Grade 12, The New AI Cognitive Framework helps students learn not just to use AI, but to challenge it, verify it, and create with it responsibly
Here's how the framework can be mapped and applied across school education:
🎯 Curate: Students find and organize information from AI and human sources.
🎯 Interpret: Students critically explain, summarize, and discuss AI outputs.
🎯 Strategize: Students plan and solve real problems using AI support.
🎯 Deconstruct: Students analyze the structure, fairness, and bias in AI content.
🎯 Validate & Innovate: Students check for originality, evaluate ethics, and create new solutions with AI collaboration.
From early sorting skills to responsible innovation, The New AI Cognitive Framework helps students grow into critical thinkers, ethical evaluators, and creative innovators in an AI-powered world.
How University Faculty Can Use The New AI Cognitive Framework
The New AI Cognitive Framework offers a dynamic, future-oriented structure for designing learning experiences, assessments, and research pathways in an AI-driven world. Faculty across undergraduate, postgraduate, and doctoral levels can integrate the framework to build critical, ethical, and innovative thinking progressively.
Undergraduate (UG) Level
At the undergraduate stage, faculty should focus on developing students’ foundational cognitive skills:
Curate: Assign tasks requiring students to find, select, and organize credible academic and AI-generated information.
Interpret: Guide students to critically understand, summarize, and reflect on diverse sources, including AI outputs.
Strategize: Engage students in applied projects where they plan and implement AI-supported solutions to structured problems.
Postgraduate (PG) Level
At the postgraduate stage, faculty should deepen students’ analytical, strategic, and evaluative abilities:
Deconstruct: Assign advanced analysis tasks, breaking down AI-generated research, academic arguments, or models.
Validate: Require critical evaluations of data authenticity, AI fairness, research originality, and ethical compliance.
Strategize: Expect strategic solution designs for real-world ambiguous problems, utilizing AI critically.
Doctoral Level
At the doctoral stage, faculty should support the creation of original, transformative knowledge:
Curate and Interpret: Require expansive, critical synthesis of AI and human-generated academic sources in literature reviews.
Deconstruct and Validate: Integrate methodological critiques and originality validations into dissertation work.
Innovate: Guide students to produce significant, publishable research outcomes or products that ethically and creatively integrate AI capabilities.
