Lesson 4: Collecting Data
Executing the plan: gathering data accurately and organizing it.
🎯 Learning Intentions
- Conduct data collection efficiently and accurately
- Use logical systems (tally marks, spreadsheets) to record data
- Troubleshoot problems during collection
🎥 Media Anchor (8 mins)
Video: Research Skills for Students
- What quality checks should happen while collecting data?
- How do we reduce errors when recording class survey responses?
1. Preparation: Data Tables (10 mins)
Before you collect, you need a place to put the answers!
Activity: Draw a data table in your workbook.
| Name (Optional) | Question 1 Answer | Question 2 Answer |
|-----------------|-------------------|-------------------|
| ............... | ................. | ................. |
| ............... | ................. | ................. |
2. Field Work: Data Collection (30 mins)
This is the main action phase! Students execute their plans:
- Circulating the room to survey classmates
- Going outside to observe (if allowed)
- Distributing digital survey links
Teacher Role: Circulate and ensure respectful interaction. Check that students are recording data, not just listening.
3. Data Quality Check (10 mins)
Review your data:
- Do you have enough responses? (Aim for 20-30+)
- Is any data messy or unclear?
- Did you miss anyone?
4. Next Steps (5 mins)
Homework: Finish collecting any missing data so you are ready to organize it in the next lesson.
📋 Teacher Planning Snapshot
Ngā Whāinga Ako — Learning Intentions
Students will engage with this resource to develop statistical investigation skills — planning inquiries, collecting and analysing data, interpreting distributions, and communicating findings. Tūhuratanga (investigation) is framed as a tool for understanding our communities and environment in Aotearoa New Zealand.
Ngā Paearu Angitū — Success Criteria
- ✅ Students can identify an investigative question, collect relevant data, and display it clearly.
- ✅ Students can interpret statistical findings and discuss what they might mean for a real-world community or environmental context.
Differentiation & Inclusion
Scaffold support: Provide structured investigation frameworks (PPDAC cycle templates) for entry-level access. Offer partially completed data tables for students who need additional support. Extend capable learners by asking them to critique a statistical claim from a news article, or to design their own community data investigation.
ELL / ESOL: Pre-teach statistical vocabulary (median, mode, range, distribution, sample, population). Pair visual representations (graphs, tables) with plain-language explanations. Allow students to discuss statistical ideas orally before writing. Encourage use of home language for initial sensemaking.
Inclusion: Statistical investigation offers natural differentiation — all students can engage with the same real-world question at different levels of mathematical complexity. Neurodiverse learners benefit from structured, step-by-step investigation processes. Use collaborative group investigation formats that distribute roles (data collector, recorder, analyst, presenter).
Mātauranga Māori lens: Tūhuratanga — the practice of careful investigation — resonates deeply with mātauranga Māori. The maramataka is a sophisticated data system: tracking environmental patterns, seasonal cycles, and ecological indicators over generations. Iwi environmental monitoring — counting kaimoana populations, tracking water quality, observing bird migrations — is applied statistical thinking. Framing statistics within community and environmental inquiry connects data to mana whenua responsibilities.
Prior knowledge: Students should have basic familiarity with data displays (bar graphs, dot plots). No prior statistical investigation experience required — the PPDAC inquiry cycle provides accessible scaffolding for first-time investigators.
Curriculum alignment
- Statistics — Statistical Investigation: Plan and conduct investigations using the statistical enquiry cycle — determining appropriate variables and data collection methods; gathering, sorting, and displaying multivariate category, measurement, and time-series data to detect patterns, variations, relationships, and trends; comparing distributions visually; communicating findings, using appropriate display.
- Statistics — Probability: Investigate situations that involve elements of chance by comparing experimental distributions with expectations from models of the possible outcomes, acknowledging uncertainty.