A complete pedagogical model for building AI fluency and metacognitive depth in 16-week disciplinary courses through structured, concurrent learning across three cognitive layers.
Five instructional stages unfold simultaneously across three cognitive layers, creating 15 distinct activation points where students encounter and apply the same mental models in evolving contexts.
Delta (Δ) = change. Iota (ι) = small. Small, incremental changes compound into genuine competence. G3 operationalizes this principle by structuring 16 weeks around five stages and three layers, creating repeated activation of mental models across different contexts.
Learning is the accumulation of repeated, structured activations, not one-time events.
All three layers develop simultaneously, accelerating schema formation and transfer.
AI fluency rooted in disciplinary thinking prevents detached, mechanical skill.
The goal is independence: students apply frameworks to novel contexts without external scaffolds.
This geometric architecture shows how domain cognition, metacognition, and AI fluency meta-schemas interact and evolve together across the five instructional phases.
What students think about (disciplinary concepts, frameworks, ways of reasoning). Without domain grounding, AI use is mechanical. G3 keeps domain thinking central throughout: students use AI as a thinking partner, not a replacement for thinking.
What students think about their thinking (awareness of cognitive processes, ability to monitor and adjust reasoning). Metacognition bridges domain knowledge and AI fluency. Students who can't articulate how they think can't evaluate AI output.
Mental models for evaluating AI: recognizing capabilities, limitations, bias, and output quality. Without explicit schemas, students either over-trust or dismiss AI. G3 builds schemas that transfer to novel tools and domains.
Each stage represents a distinct learning context, with the same mental models applied in new ways across all three layers.
Establish baselines. Across all three layers, students see where they begin.
Model all three layers. Instructor demonstrates domain reasoning, metacognitive thinking, and AI critique. Students learn with structured guidance.
Practice with scaffolds in place. Students apply frameworks in collaborative contexts; all support structures remain available.
Work independently. Scaffolds are removed; students operate with internalized schemas and judgment.
Synthesis and transfer. Students demonstrate integrated learning and plan forward applications.
Two core tools your students will master: ANCHOR for writing prompts to AI, and AUDIT for evaluating AI output.
What specific task or action do you want the AI to perform?
What context, background, or story does the AI need?
What are the boundaries? (format, length, tone, audience)
Why does this task matter? What's your stake in it?
What is your desired end result? What does success look like?
Why are you asking this question? What problem are you solving?
Does the output match what you asked for?
Are the facts accurate and verifiable?
Does this extend or deepen your thinking?
What would you change or improve?
How would you apply this differently elsewhere?
Start by mapping your existing course activities to the G3 framework. Identify where you model, where students practice, and where they work independently. Then layer in explicit scaffolds for all three cognitive dimensions simultaneously.
What do students already know about the domain, their own thinking, and AI? Use diagnostic activities across all three layers.
Show domain reasoning with think-alouds. Model metacognition explicitly. Critique AI outputs alongside students, naming your judgment process.
Provide frameworks and rubrics. Students practice with all supports. Use ANCHOR for prompt design; introduce AUDIT for evaluation.
Remove scaffolds progressively. Capstone projects require integration across all three layers. Students demonstrate autonomous competence.
G3 integrates AI instruction into existing disciplinary courses without creating a separate AI track. It scales across departments by giving every instructor a common pedagogical architecture and shared frameworks (ANCHOR, AUDIT) that students encounter consistently.
The complete framework includes theoretical foundations, detailed layer-stage intersections, implementation case studies, assessment rubrics, and a full instructional guide.
Download the Complete Framework (PDF)