# Optional Week 2 data-dialogue studio

Five independent 35-minute sessions. Use the [studio learner cards](student-materials.md), [English A/B](../../english/term-1/weeks-01-02/student-materials.md), [Maths Card B](../../mathematics/term-1/weeks-01-02/student-materials.md), [accessible visual/text pair](../print/text-alternatives.md) and [separate teacher key](teacher-key.md). Each block is 4 + 7 + 9 + 8 + 5 + 2 minutes. Schedule **Day 10 after both subject Day 10 checks**; earlier use would disclose the fresh materials. No integrated result substitutes for subject assessment.

## Day 6 — Six points, many stories

**Success:** State what Card B's scatterplot shows and name a different question the English letters ask.

1. **Open · 4 min.** Read (3 hours, 9 visits) as one paired fictional weekend; ask what the point does and does not represent.
2. **Model · 7 min.** Put x hours and y visits on axes; narrate two coordinates. Contrast “number of visits during hours” with “whether a visitor can get home”.
3. **Build · 9 min.** Learners plot all six pairs or use the coordinate list to produce a verbal/tactile pattern description.
4. **Test · 8 min.** One learner voices the graph, another voices Text B's transport concern. Find the point in the graph that proves an accessible journey. There is none.
5. **Apply · 5 min.** Write one data sentence and one question for a board that needs both use and access evidence.
6. **Exit · 2 min.** Check for paired axes, units and “not measured”. If learners infer unique people, revisit Card B's count definition.

## Day 7 — Does a graph have a headline?

**Success:** Draft an honest graph caption that includes direction and a scope limit.

1. **Open · 4 min.** Compare “More hours always mean more visits” with the points from x=2 to 3 and x=4 to 5.
2. **Model · 7 min.** Draft “Six invented weekends show a generally upward, roughly linear pattern between later-opening hours and visits during those hours.” Explain each qualifier.
3. **Build · 9 min.** Learners write or speak their own caption and alt text; all six coordinates remain available in the text table.
4. **Test · 8 min.** Peers circle words implying causation, perfect fit or a real population. Revise with a conditional or scope phrase.
5. **Apply · 5 min.** Link the caption to one exact sentence in A or B; explain what that text asks beyond the graph.
6. **Exit · 2 min.** Collect caption and connection. Revisit an axis label before rhetoric if the graph itself is misread.

## Day 8 — A strong number can be a narrow number

**Success:** Interpret *r* ≈ +0.919 and explain why an argument still needs source context.

1. **Open · 4 min.** Ask learners to predict sign from the plot, then show the technology result for Card B after subject calculation.
2. **Model · 7 min.** Say “strong positive linear association among six invented pairs”; deliberately reject “strong proof that later hours cause visits”.
3. **Build · 9 min.** Learners add a footnote to a fictional slide: variable labels, six-weekend scope, technology used and one missing condition.
4. **Test · 8 min.** Read Text A's “could tell us who arrives”. What does this dataset count but fail to identify? It counts visits, not who the visitors were.
5. **Apply · 5 min.** Replace one overconfident slide title with a bounded title suitable for a public meeting.
6. **Exit · 2 min.** Collect title and footnote. If *r* is read as a fraction of people, revisit what Pearson's *r* quantifies.

## Day 9 — What does 84.4% buy us?

**Success:** Explain *R*² ≈ 84.4% without turning explained variation into a causal claim.

1. **Open · 4 min.** Ask if 84.4% means that 84.4% of visitors wanted later hours. It does not.
2. **Model · 7 min.** Relate *R*² to how closely a straight-line relation accounts for observed variation in y around its mean, limited to Card B's six pairs.
3. **Build · 9 min.** Learners write a paired public note: one sentence on the model description, one on what the letters and data still do not settle.
4. **Test · 8 min.** Peer checklist: Does the sentence name y, scope, line and non-causal boundary? If any are absent, revise only that part.
5. **Apply · 5 min.** Use Card S4's claim ladder to place the *R*² sentence on a rung. It is a computed model summary, not direct proof of a policy outcome.
6. **Exit · 2 min.** Collect the revision and a proposed real-world check. Next lesson targets the missing dimension.

## Day 10 — Publish a careful draft

**Success:** Produce a short fictional public update that keeps text, table and graph claims in their own evidence lanes.

1. **Open · 4 min.** **Only after both subject checks:** students may now revisit English [Text C](../../english/term-1/weeks-01-02/fresh-text-c.md) and maths [Card C](../../mathematics/term-1/weeks-01-02/fresh-data-c.md). Make clear that an integrated revision is separate from first independent responses.
2. **Model · 7 min.** Use Card S5 to plan four parts: proposed decision; exact observation; counter-question; a way to collect better input. Do not provide a completed library answer.
3. **Build · 9 min.** Learners draft a 120–160 word notice or equivalent accessible spoken/AAC notice. They may choose one original text and one numerical card; they must name the source and fictional scope.
4. **Test · 8 min.** Partners act as board reviewer and resident reader. They mark unsupported population claims, missing denominators, inaccessible response routes and claims attributed to the wrong source.
5. **Apply · 5 min.** Learners revise a headline or sentence and write a one-line change note: “I changed ___ because the evidence shows ___.”
6. **Exit · 2 min.** Save both drafts. Use the teacher key to select the next subject-specific move; never award a QCAA result from this cross-subject work.

**Rights:** Original studio scripts © NeuroForgeIO Pty Ltd 2026, [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/).