Day 7 · Dimension 7 · ~5 hrsnew in v5
Equity-Centred Extension Practice
Who Gets to Anchor — Equity-Centred Extension Practice
D7 asks whether the teacher's AI practice supports ALL learners as anchoring agents, not just the advantaged. The critical discriminator between Level 2 and Level 3 is whether the teacher has moved from "all students can access this AI" to "all students benefit equally from this AI" — and can name, specifically, who does not. Generic inclusivity language ("meet diverse needs") cannot score above Level 2.
Level 1–2
Effect map uses generic groups ("diverse learners"). Redesign adds accommodations without structural change. Representation audit lists abstract bias categories. Anchoring plan targets a category, not named students.
Level 3
Effect map names specific groups in your class with evidence. Redesign is structural with theory of change. Representation audit traces ≥3 specific gaps to classroom consequences. Cultivation plan names specific students with observable success signals.
Level 4
Effect map surfaces an effect you would not have predicted. Redesign is tested and honestly reported. Audit reveals a gap the teacher would not have seen before this unit. Anchoring plan distinguishes anchoring capacity from AI skill with a specific case.
4 TASKS What you will produce on Day 7
01
Differential-Effect Map
The HAA axiom says every learner should be supported as an anchoring agent for their own AI-extended learning. But the conditions under which different learners can actually anchor are unequal — shaped by language, socioeconomic status, disability, cultural familiarity with AI norms, and representation in training data. This task asks you to make those differential conditions concrete for YOUR class. Named learner groups; named differential effects; named evidence.
Key concepts:
- Access ≠ benefit. Every student having the AI available does not mean every student gains equally from it
- Name the differential — EAL, SEN, neurodivergent, cultural background, prior AI exposure — not "diverse learners"
- Evidence base required: what did you observe, read, or test that grounds the claim about this group?
What good looks like: ≥3 specifically named learner groups in your actual class. Each row ties an AI use to a differential effect with evidence. Level 4 identifies an effect you would not have predicted — something the mapping exercise itself revealed.
Evaluation criteria: D7.1 Recognition of Differential Extension Effects
02
Inclusive Redesign
Diagnosis without redesign leaves the inequity in place. This task asks you to act on one finding from p7t1. The redesign must be structural — a change to how the activity is set up, not a bolt-on accommodation. "I'll offer support if they ask" is not a redesign; "I've restructured the task so the AI output is the starting point for discussion rather than the deliverable" is.
Key concepts:
- A redesign changes the activity's structure, not just its accommodations
- Theory of change: explain WHY the redesign is expected to close the gap, not just that it will
- Don't default to the modal learner — the redesign should genuinely serve the originally-disadvantaged group, ideally without disadvantaging others
What good looks like: Original activity, specific redesign, theory of change linking them. The redesign is structural, not cosmetic. Level 4 tests the redesign, even informally, and reports on whether the theory held.
Evaluation criteria: D7.2 Inclusive Extension Design
03
Training-Data Representation Audit
AI outputs reflect the data they were trained on. Representation gaps — whose contexts are present, whose dialects are mishandled, whose histories are taken as canonical — are not abstract ethics; they have specific pedagogical consequences in your specific unit. This task asks you to surface those gaps in one AI output and trace each to the classroom. The audit is subject-specific: a history teacher's gaps look different from a maths teacher's.
Key concepts:
- Representation gaps are pedagogical risks, not just ethical ones — they shape what students take as normal
- ≥3 specific gaps named in one AI output (not generic "AI is biased")
- Each gap traced to its consequence in your subject — the misconception it reinforces, the voice it silences, the curriculum point it distorts
What good looks like: One specific AI output under audit. ≥3 named gaps. Each traced to a classroom-level pedagogical consequence. Level 4 identifies a gap that the teacher would not have seen before this unit — genuine learning-through-auditing.
Evaluation criteria: D7.3 Distributed Anchoring Capacity
04
Anchoring-Capacity Cultivation Plan
Anchoring capacity — the disposition and skill to exercise agency over AI — is itself unevenly distributed. Students who come in with less prior AI exposure, less confidence challenging authoritative-sounding output, or cultural norms of deference may find it harder to anchor even when given identical tools. This task asks you to plan a genuine cultivation — not a one-off lesson on "how to use AI critically", but a sustained approach to building capacity in specific students who need it.
Key concepts:
- Anchoring capacity ≠ AI skill — you can be fluent with AI and still defer to it
- Named specific learners (initials); specific interventions; specific success signals
- Don't plan on behalf of a category ("the EAL learners") — plan on behalf of specific students you know
What good looks like: Specific learners named (initials). Interventions are sustained, not one-off. Success signals are observable and not proxies for tool use. Level 4 distinguishes anchoring capacity from AI skill — names a student who is fluent with AI but defers to it, or a student who is cautious with AI for the right reasons and does not need an intervention.
Evaluation criteria: D7.1 Recognition of Differential Extension Effects
3 SUB-COMPETENCIES Evaluation criteria for Day 7
D7.1
Recognition of Differential Extension Effects
General across Types A–F
1 — Nascent
Generic awareness. are differential effects named specifically, or collapsed into "diverse learners" — not yet asked. Effect map uses generic groups ("diverse learners"). Redesign adds accommodations without structural change. Representation audit lists abstract bias categories. Anchoring plan targets a category, not named students.
2 — Developing
Partial demonstration. Effect map uses generic groups ("diverse learners"). Redesign adds accommodations without structural change. Representation audit lists abstract bias categories. Anchoring plan targets a category, not named students.
3 — Proficient
Full demonstration. Effect map names specific groups in your class with evidence. Redesign is structural with theory of change. Representation audit traces ≥3 specific gaps to classroom consequences. Cultivation plan names specific students with observable success signals.
Anchor: ≥3 specifically named learner groups in this class; each row has evidence.
4 — Advanced
Effect map surfaces an effect you would not have predicted. Redesign is tested and honestly reported. Audit reveals a gap the teacher would not have seen before this unit. Anchoring plan distinguishes anchoring capacity from AI skill with a specific case.
For each major AI use in your unit, map its differential effect across ≥3 named learner groups in your actual class. Each row: AI use, learner group (EAL / SEN / neurodivergent / culturally under-represented / socioeconomically disadvantaged / etc.), the differential effect, and the evidence you base it on.
Plan how you will cultivate anchoring capacity in learners who came to your class with less AI exposure or lower confidence exercising agency over AI. Name specific learners (initials only), specific interventions, and how you will know it's working.
D7.2
Inclusive Extension Design
Central for Types A/C/D
1 — Nascent
Generic awareness. is the redesign structural, or a bolt-on accommodation — not yet asked. Effect map uses generic groups ("diverse learners"). Redesign adds accommodations without structural change. Representation audit lists abstract bias categories. Anchoring plan targets a category, not named students.
2 — Developing
Partial demonstration. Effect map uses generic groups ("diverse learners"). Redesign adds accommodations without structural change. Representation audit lists abstract bias categories. Anchoring plan targets a category, not named students.
3 — Proficient
Full demonstration. Effect map names specific groups in your class with evidence. Redesign is structural with theory of change. Representation audit traces ≥3 specific gaps to classroom consequences. Cultivation plan names specific students with observable success signals.
Anchor: Original → redesign → theory of change. Redesign changes the activity's structure.
4 — Advanced
Effect map surfaces an effect you would not have predicted. Redesign is tested and honestly reported. Audit reveals a gap the teacher would not have seen before this unit. Anchoring plan distinguishes anchoring capacity from AI skill with a specific case.
p7t2Inclusive Redesign
Take ONE row from p7t1 where you identified a disadvantaged group, and redesign the AI activity so that group is no longer structurally disadvantaged. Document the original, the redesign, and a theory of change linking the two.
D7.3
Distributed Anchoring Capacity
Cross-cutting; primary for Type C
1 — Nascent
Generic awareness. does the plan target specific named students with observable success signals — not yet asked. Effect map uses generic groups ("diverse learners"). Redesign adds accommodations without structural change. Representation audit lists abstract bias categories. Anchoring plan targets a category, not named students.
2 — Developing
Partial demonstration. Effect map uses generic groups ("diverse learners"). Redesign adds accommodations without structural change. Representation audit lists abstract bias categories. Anchoring plan targets a category, not named students.
3 — Proficient
Full demonstration. Effect map names specific groups in your class with evidence. Redesign is structural with theory of change. Representation audit traces ≥3 specific gaps to classroom consequences. Cultivation plan names specific students with observable success signals.
Anchor: Specific learners named (initials); interventions sustained; success signals observable.
4 — Advanced
Effect map surfaces an effect you would not have predicted. Redesign is tested and honestly reported. Audit reveals a gap the teacher would not have seen before this unit. Anchoring plan distinguishes anchoring capacity from AI skill with a specific case.
Pick ONE AI output in your subject (a generated example, explanation, or scenario) and audit it for representational gaps. Document ≥3 specific gaps — whose contexts/dialects/histories are present or absent — and trace each to a pedagogical consequence in your unit.