Teacher guide — Grade 11, Unit 7: Maps and geospatial thinking¶

Time: 3 lessons + project (about 5 periods). Track: B (code, light).

#	Lesson	Time
1	Coordinates and distance	40–45 min
2	Maps that don't mislead	40–45 min
3	Open map data and licences	40–45 min
P	Unit project: Where is it worst?	2 periods

Before you start¶

Materials: Notebook notebooks/geo_basics.ipynb; optional OSM data via Overpass (internet).
Read docs/pedagogy/lesson-anatomy.md and docs/pedagogy/ai-use-policy.md.

If you have no computers / no internet¶

Use a printed map and string to compare straight-line and road distances.

Common misconceptions¶

Colour maps of counts mislead; use rates.
Straight-line distance = travel distance in the hills.

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: Coordinates and distance 1. Latitude measures…
Answer: North–south position. 2. Straight-line vs road distance in hills?
Answer: Road is longer. 3. What does haversine compute?
Answer: Distance along the Earth's surface between two points.

Lesson 2: Maps that don't mislead 1. Count or rate for a choropleth?
Answer: Rate. 2. Why colour-blind-friendly scales?
Answer: Many people can't tell red from green. 3. What to show for missing data?
Answer: A distinct colour/pattern and a legend note.

Lesson 3: Open map data and licences 1. Credit line for OSM?
Answer: © OpenStreetMap contributors. 2. Does 'open' mean 'no conditions'?
Answer: No: check the licence. 3. Why check boundary licences?
Answer: They may differ from the map data.

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 11–12 Computer Science (databases, programming) and Maths/Statistics.

Answers: practice exercises¶

(27.7, 85.3) = latitude 27.7° N, longitude 85.3° E — Kathmandu. (85.3, 27.7) read as lat/lon is near the North Pole region (85.3° N) — a swapped-coordinate bug.
≈ 222 km; ≈ 2 × 98 = 196 km.
≈ 832 km straight line; highway ≈ 1,000 km → ratio ≈ 1.2 (the Terai is flat; hill routes have far higher ratios).
Nearest synthetic station ≈ 30 km from Kathmandu (PM2.5 82.1); 11 stations within 150 km, mean PM2.5 ≈ 92.5 (all synthetic, with an invented west–east gradient).
Equal intervals (width 20.75 from 12 to 95): 7, 1, 1, 1 → only 1 district in the top class. Quantiles (breaks ≈ 15, 17, 31.75): 2–3 districts per class → 3 in the top class (35, 60, 95). Quantiles exaggerate the gap between 16 and 18.
The large district's rate (based on 1,200 cases) is far more reliable; the small district's 75 could be 25 or 125 next year by chance. Show counts, use multi-year rates, or mark low-population districts.
Density divides by area: small crowded districts (Kathmandu valley, Terai) stand out; a count map highlights big populations; area bias differs. Each answers a different question.
Layers: schools and health posts (OSM, ODbL), roads/footpaths (OSM), palika boundary (HDX, check licence); method: network travel time or at least straight-line distance; limits: unmapped facilities, seasonal roads, facility opening hours/staffing.
If the combined database is published (publicly used), it must be offered under ODbL (share-alike) with credit; the private data mixed into it would become subject to that.

Real-data exercises: notes¶

R1 The aftershock zone extends east of the Gorkha epicentre towards Dolakha/Sindhupalchok (the 12 May 7.3 quake); most events are within ≈ 50–150 km of Kathmandu.
R2 Koshi basin generally has the most potentially dangerous lakes in the ICIMOD 2020 inventory — check the file.
R3 Requires internet and geopandas; expect name mismatches after the 2015 restructuring.