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A practical framework for secondary education
The Learning Intelligence Framework
Helping secondary students learn, use, and create with AI without outsourcing their thinking.
The important question is no longer whether students use AI, but whether their use preserves and develops their capacity to think.
AI changes what students can produce.
Great teaching changes what students are asked to think.
Start here
What is this?
Designed for secondary-school learners, the Learning Intelligence Framework (LIF) helps students learn, use, innovate, and develop insight while building AI literacy, creativity, responsibility, and sound judgment.
Students learn to question information, verify results, document their process, revise their work, and remain responsible for what they create.
Developed in an Ontario secondary-school classroom, the framework is designed to be useful to educators wherever they teach.
Students still need fundamental knowledge of the subjects they are studying. They also need to understand what AI means within the context of each subject. LIF helps students decide when to use AI, when not to use it, and how to remain responsible for their thinking, choices, and learning.
Download the one-page LIF overviewUse
Apply tools with purpose. Verify, evaluate, and make responsible choices.
Innovate
Create new ideas. Solve problems. Make an impact.
Insight
Reflect on decisions. Name the learning. Carry understanding forward.
Temporary support. Lasting capability. Students move from guided support toward increasingly independent judgment, skill, and creative ownership. Cognitive ownership means students can explain, question, adapt, and defend the thinking behind their work—even when AI helped them produce it.
The core idea behind the work
Think critically. Create responsibly. Adapt confidently.
LIF develops durable habits: inquiry, verification, revision, reflection, and ethical decision-making that remain useful as technologies change.
This requires more than AI fluency. Students need AI intuition: the ability to use it, verify it, judge it, and know when their own knowledge, observation, and judgment must lead.
Video introduction
Watch the Overview
A short introduction to the Learning Intelligence Framework, and why student thinking, judgment, and process matter in the age of AI.
Watch on YouTubeExplore the three modulesLearn · Use · Innovate · Insight
The Three Learning Modules
A simple framework. A powerful mindset.
Module 01
AI, Media & Learning Intelligence
How we use intelligent tools without outsourcing thinking.
Explore Module 01
The goal: Technology moves fast, but human judgment comes first. Students learn to use AI as a coach, not a crutch.
Core mindset
- Director and Intern: AI works quickly, but the student brings taste, judgment, direction, and responsibility, and owns the final submission.
- The S.E.E. Filter: Before using AI, students ask whether the use is Safe, Ethical, and Effective.
- Four LIF phases: Learning moves through Learn → Use → Innovate → Insight.
What students explore
- AI Explained: Why AI is a prediction engine, not a brain with understanding.
- Deepfakes and Verification: Why looking at an image is no longer enough, and how to verify sources upstream.
- The Biometric Red Line: Non-negotiable boundaries around privacy, consent, and identity.
- The D.S.D. Checklist: Declare AI use, Show prompts, and Demonstrate verification and revisions.
Assessment example from my classroom
- 70% Process and Thinking: direction, questioning, verification, revision, and refinement.
- 30% Final Product: the work that was ultimately generated.
“If the AI does the pushups, you don’t get the muscles.”
Module 02
The Learning Intelligence Workshop
How we should think about AI.
Explore Module 02
The goal: Shift the question from “How do I use AI?” to “How should I work with AI?” so students remain in control, aware, and creative, not passive passengers.
Core mindset
- Coach vs. Crutch: Guided AI can support a performance boost while preserving independent skill and judgment.
- Director vs. Intern: The AI intern brainstorms and works quickly; the student directs the vision, makes decisions, and takes responsibility.
- Thinking over Prompting: AI does not simply need better prompts; it needs better thinkers.
- Strategic Friction: Build deliberate moments where students think, decide, explain, or verify before AI carries the work forward. Preserve the cognitive effort that develops skill and judgment, without making AI harder to use. Put this into practice through Initial Thinking → AI Challenge → Human Decision → Verification.
What students explore
- Who Is Doing the Thinking?: Examine what students actually learn when AI writes the first draft or solves the hardest part.
- Authorship and Ownership: Explore what makes work truly yours when prompting alone is not authorship.
- Intentional Boundaries: Ask not only whether AI can be used, but whether it should be used.
- The AI Footprint: Evaluate trade-offs ranging from energy and water use to potential breakthroughs in medicine.
- Becoming the Experts: Develop better questions instead of searching only for easy answers.
Assessment focus
- Process over Product: process documentation and human decisions are made visible.
- Creative Ownership: the grade reflects the meaningful choices the student made.
Signature learning experience
Expert Panel Investigation
The golden rule: the job is not to find a quick answer; it is to become a better thinker. Gemini is used as a discussion partner that debates, challenges, and tests ideas, not as an answer machine.
Five expert panels
- Human Thinking: Who is doing the thinking: you or the AI?
- Creativity: What makes something “your work”?
- Trust & Responsibility: When should humans trust AI?
- Sustainability: Is AI good for the planet?
- Future of Work: What skills matter most in an AI world?
Visible thinking process
- Initial Thinking: establish the panel’s starting perspective.
- Gemini Challenge: ask AI to debate, challenge, or test the group’s ideas.
- Final Position: explain how the group’s view evolved.
- Remaining Question: identify what the panel is still wrestling with.
Workshop exit ticket
Students identify their panel and respond in 3–5 sentences to one prompt:
- One idea that changed my thinking today…
- One idea I’m still thinking about…
- One question I still have…
Assessment: individual depth of thinking, not agreement with a predetermined answer.
“AI helps you create. You decide what matters.”
Module 03
Creative Intelligence
How we work with AI without surrendering voice, judgment, or authorship.
Explore Module 03
The goal: Master multi-tool workflows and use metacognition (thinking about your thinking) to direct high-level AI media productions without losing creative voice.
Core mindset
- Creative voice stays central: AI supports the production, but human taste, judgment, and vision remain at the centre.
- The Director’s Playbook: Students tell AI the goal, then ask it to interview them with 10 or more questions before proposing a solution.
- Metacognition: Students use AI as a thought partner to refine ideas while remaining conscious of their own decisions.
What students explore
- The Creative AI Landscape: Explore leading tools and study how professionals produce AI-assisted commercials and cinematic trailers.
- Multi-Tool Production Workflows: Connect AI scripting, consent-based synthetic voice workflows where permitted, video generation, and video editing into a coherent production pipeline.
- Metacognition and Human Vision: Use AI to challenge and strengthen ideas without surrendering authorship.
- The Interview Prompt Strategy: Replace the quick request with a guided discovery process that produces more intentional results.
“Don’t start with a simple prompt. Start with your goal, and make the AI ask better questions.”
Classroom practice · See the evidence
From framework to real classroom work
See how assignments, Design & Skills Documents, Trust Audits, and student reflection make creative decisions and learning visible.
Production-ready D.S.D.Assets, AI delegation, verification, and reflection
D.S.D. LitePrompts, revisions, visual proof, and integrity
Authentic student evidenceEditing choices, Trust Audit, and reflectionExplore Classroom Practice
Looking for academic-integrity guidance? Explore the Teacher Guide →
Why This Matters
AI is increasingly able not only to produce polished work, but to perform parts of the thinking process itself: exploring possibilities, building models, planning steps, and solving problems. Teachers therefore need stronger ways to ensure students continue developing knowledge, judgment, understanding, and the ability to explain and defend their decisions.
The goal is not AI-proof assessment. The goal is learning-rich assessment.
For me, this work began with a personal question about my own children and my students: What will they need to do, and who will they need to become, in a world shaped by AI? Since 2022, that question has led me to experiment with ways of helping students think more, not less, with this technology.
Sources & context
Built for thoughtful, responsible practice
Explore selected research, books, institutional guidance, and professional learning that have informed this framework.
View all Sources & EvidenceMIT
RAISE
Research, education, and outreach supporting responsible AI literacy.
HarvardProject Zero
Research-based frameworks that deepen thinking, learning, and understanding.
StanfordCRAFT
Classroom-ready AI literacy resources co-designed with secondary-school teachers.
These links provide relevant context; they do not imply endorsement of the Learning Intelligence Framework.