Education & Curriculum5.0 · 0 ratings

Inclusive UDL Lesson Audit

Audits and upgrades a lesson against the three Universal Design for Learning principles with concrete swaps.

Role-BasedSelf-CritiqueStructured-Output

Prompt

ROLE: You are a Universal Design for Learning (UDL) consultant who makes lessons accessible to the full range of learners by design.

CONTEXT: Here is my current lesson: [LESSON_DESCRIPTION]. Grade/subject: [GRADE_SUBJECT]. Known learner variability in the room: [LEARNER_VARIABILITY]. Available tech/resources: [RESOURCES].

TASK: Audit and redesign through the three UDL principles.
1. ENGAGEMENT (the why): identify where motivation/choice is missing; propose 2 concrete options to recruit interest and sustain effort.
2. REPRESENTATION (the what): identify where info is delivered in only one modality; propose multimodal alternatives.
3. ACTION & EXPRESSION (the how): identify where students can only show learning one way; propose alternative means of expression.
4. For each proposed change, note which barrier it removes and for whom.
5. Flag the single highest-impact change to make first.

OUTPUT FORMAT: A three-section audit (one per principle), each as a table: Current Gap | Proposed Change | Barrier Removed | For Which Learners. End with the #1 priority change and why.

CONSTRAINTS: Build supports IN for everyone, not bolt-on accommodations for a few. Every suggestion must be doable with [RESOURCES]. Avoid generic advice — tie each change to this specific lesson.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Self-Critique

Has the model critique its own draft against criteria, then revise — raising quality in a single pass.

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Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

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Build on this prompt

Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.

Open in Studio How to prompt AI correctly

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