Learning design
Ask AI for lesson options or examples, then judge them against the objective, learner context, accessibility needs, and available evidence.
Apply: use AI to improve teaching practice
Use AI in a bounded instructional workflow while the teacher retains learning goals, domain judgment, assessment integrity, and responsibility for the learner.
Assess your starting pointChoose an instructional workflow
Feedback
Use AI for a bounded first pass. The teacher checks accuracy, tone, developmental fit, and the next useful intervention.
Assessment
Redesign tasks so the evidence still measures student understanding, even when AI assistance is allowed or expected.
Run the AAOS method on instruction
- Diagnose: name the learning goal, learner need, and instructional problem.
- Activate: select the AI role, approved inputs, and boundary for assistance.
- Control: review privacy, bias, accessibility, accuracy, age appropriateness, and assessment integrity.
- Execute: draft, ground, validate, teach, observe, and revise.
- Measure and scale: compare learner evidence and teacher correction load before sharing the practice.
For consequential feedback, placement, or handoffs, use an Instructional Integrity Packet to record the outcome, assumptions, evidence, validation status, ownership, and risk.
What good looks like
- The learning objective remains clear before AI is introduced.
- AI-generated claims and materials are checked against appropriate sources.
- Students know what AI use is permitted and what evidence of learning they must show.
- The teacher can explain why the final instructional decision is appropriate for this learner or class.
Avoid this
Do not let AI obscure student understanding or turn a useful draft into an unreviewed instructional decision. Review depth should increase with consequence.
Continue your path
Return to the teacher path, get guided support, or see the assignment redesign example. Use AAOS to connect the workflow to the full operating model.
Take the assessment