Teacher guide — Grade 12, Unit 7: Communicating with data¶

Time: 3 lessons + project (about 5 periods). Track: A/B.

#	Lesson	Time
1	Action titles and honest charts	40–45 min
2	The one-page memo	40–45 min
3	Presenting and publishing	40–45 min
P	Unit project: Story and memo	2 periods

Before you start¶

Materials: Notebook notebooks/data_story.ipynb; memo template in docs/templates/policy-memo.md.
Read docs/pedagogy/lesson-anatomy.md and docs/pedagogy/ai-use-policy.md.

If you have no computers / no internet¶

Write the memo on paper; draw the chart by hand.

Common misconceptions¶

More charts = more convincing.
Hiding uncertainty makes you more credible (it does the opposite).

Differentiation¶

Support: give a partially filled table / sentence starters; pair with a data-steward role.
Stretch: ask "what would change your conclusion?" and "who is missing?"

Answer key (check questions)¶

Lesson 1: Action titles and honest charts 1. What is an action title?
Answer: A title that states the finding. 2. What goes in the caption?
Answer: Source, units and a limit. 3. Why a zero baseline for bars?
Answer: Otherwise differences look exaggerated.

Lesson 2: The one-page memo 1. What goes first?
Answer: The bottom line. 2. Why say what you don't know?
Answer: It builds trust and helps decisions. 3. Who is your audience?
Answer: A specific decision-maker, not 'everyone'.

Lesson 3: Presenting and publishing 1. How to show uncertainty plainly?
Answer: Use a range and a sentence like 'likely between X and Y'. 2. What do you publish with data work?
Answer: Licence, credits, source, limits. 3. Is Django required?
Answer: No: optional stretch.

Assessment¶

Starter quiz each lesson (3 questions, one recalling the previous lesson); unit quiz in quiz.yml; project marked with the rubric in docs/pedagogy/assessment.md; 2-minute oral check per group.

Alignment¶

Enrichment aligned to NEB Grade 12 Computer Science (programming, databases, emerging technologies) and Maths/Statistics. Django (optional stretch): a student who knows HTML can turn the dashboard into a Django view — not required.

Answers: practice exercises¶

e.g. "PM2.5 is highest from November to February, almost every day above the national standard".
What is shown (with units), the source and date, and a limit (plus "synthetic" when relevant).
"Each extra antenatal visit goes with about 40% higher odds of delivering in a facility."
Horizontal bars sorted from highest at top read more easily (labels fit, eyes scan down a ranked list).
"Province 6 has the highest share of people living abroad (94 per 1,000). We recommend starting migrant-family support there."
Facility-delivery rates with bootstrap 95% intervals (Grade 11 Unit 3): Mountain 0.33 (0.25–0.40), Hill 0.42 (0.39–0.46), Terai 0.49 (0.45–0.53). Action title: "Mountain mothers are least likely to deliver in a facility (synthetic data)".
"Roads © OpenStreetMap contributors (ODbL); district boundaries: OCHA/HDX from Survey Department of Nepal [licence as on page]; population: National Statistics Office, Census 2021."
Assess with the checklist: right chart, sorted, honest scale, highlight, declutter, caption.
e.g. "We could not detect a change in monsoon rainfall over these 30 years; year-to-year swings are larger than any trend. Plans should prepare for both very wet and very dry years."
Chairperson: bottom line + action; newspaper: hook + human angle + the number + caution. Discuss what was lost and gained.

Lesson memo (synthetic): Province 6 districts range from Hill-02 (106.6 per 1,000) to Mountain-16 (53.1).

Real-data exercises: notes¶

R1 Absent-population shares vary greatly between real districts and provinces; let students find the pattern in the census tables themselves and compare it with the synthetic story (it will differ — that is the point).
R2 Insist on plain language and a range.
R3 Use OWID's chart page source line in the caption.