Inclusive AI Teaching Patterns

These are practical, repeatable teaching moves you can use across levels, subjects, and delivery modes.

They are designed to reduce exclusion, increase clarity, and *keep human relationships at the *centre.

Think of them as patterns, not rules — tools you can adapt to your own context.

1. The Dual-Mode Task Pattern

Every task can be completed with AI or without AI.

Why it matters:

Reduces shame for those with limited access; removes pressure for those who don’t want to use AI.

How it works:

• Version A: “With AI — critique, adapt, reflect”

• Version B: “Without AI — build from scratch, reflect on process”

What to say:

“Choose the mode that works for your learning style — both are valid.”

2. The Process-First Pattern

Shift marks toward the thinking steps, not the final product.

How to structure:

• Step 1: Plan

• Step 2: Try an AI draft (optional)

• Step 3: Annotate strengths + weaknesses

• Step 4: Rewrite using personal insight

Outcome:

You see the learner — not the model — in the work.

3. The Think-Aloud Pattern

Use voice notes or short videos for explanation.

Why:

Brilliant for ESOL, neurodivergent, or anxious writers.

Prompt:

“Talk me through the decisions you made. What did you keep? What did you change?”

Effect:

Authenticity becomes audible.

4. The Correct-the-AI Pattern

Put the learner in the seat of authority.

Activity:

Provide an AI-generated answer. Ask learners to:

• Identify errors

• Add cultural context

• Improve clarity

• Bring in lived experience

Teachable moment:

“See? You already know more than the model.”

5. The Localisation Pattern

Ground tasks in place, community, and identity.

Examples:

• “Explain this concept using a local example.”

• “Rewrite this text so it fits your whānau or workplace context.”

• “How would this idea work in Aotearoa?”

Outcome:

AI output becomes a starting point, not a worldview.

6. The Scaffolded Prompt Pattern

Teach prompts in small steps:

• Clarify task

• Set role

• Define audience

• Set constraints

• Reflect and revise

Why:

Reduces overwhelm; builds critical literacy.

7. The Layered Resource Pattern

Provide materials in multiple forms:

• Plain-language summary

• AI-expanded version

• Visuals

• Examples from diverse communities

• Step-by-step guidance

Learners choose the format that matches their cognition.

8. The Care-Centred Check-In Pattern

Before an AI-heavy task, ask:

• “How are you feeling about using AI today?”

• “What support do you need?”

• “What part feels confusing?”

Impact:

Turns AI from a pressure point into a conversation.

Kaupapa Māori Lens — Te Ara Tika o te Whakaako

Here’s the optional Māori-centred layer that deepens inclusive practice without repeating earlier pathways.

🪶 Four Inclusive Teaching Patterns Through a Kaupapa Māori Lens

1. Ako as Reciprocal Learning

Position AI as a third partner in the learning relationship — not the authority.

Try:

Learners and kaiako co-create a prompt, test it, critique it, and reshape it.

Outcome:

Ako becomes visible — learning flows both ways.

2. Whanaungatanga Through Shared Interpretation

Use AI as a discussion starter, not the final word.

Try:

“Here’s what AI said — what would our community say? What would your kaumātua say?”

Outcome:

Voices of place and lineage return to the centre.

3. Mana as Voice Protection

Encourage learners to preserve their voice, not overwrite it.

Try:

“Keep the phrasing that sounds like you — replace the rest.”

Outcome:

Mana motuhake stays intact.

4. Kaitiakitanga of Knowledge Boundaries

Teach learners to recognise when content is tapu or inappropriate for AI input.

Try:

“Is this something that belongs in a machine? Or is this for people only?”

Outcome:

Respect for cultural boundaries becomes part of digital literacy.