Seminar focus: test the strength of a conclusion
Ākonga rank sample conclusions from description to defensible inference. In seminar, they challenge unsupported certainty, distinguish sample from population, and revise wording to match the available evidence.
- Seminar move: Conclusion continuum, cross-examination, and precision rewrite
- Seminar outcome: A carefully bounded conclusion with an explicit limitation
🎯 Learning Intentions
- Interpret data to make statements
- Write a conclusion that directly answers the investigative question
- Identify limitations in the data
Use the Conclusion section of the project brief to draft and improve the final claim.
🎥 Media Anchor (8 mins)
Video: Research Skills for Students
- What level of evidence is enough to support a class conclusion?
- How do we avoid over-claiming from a small sample?
1. "I Notice, I Wonder" (10 mins)
Look at your graphs and tables. Complete these sentences:
- "I notice that most students..."
- "I notice that the difference between..."
- "I wonder why..."
Example: "I notice that 80% of students bring lunch from home. I wonder if this changes in winter?"
2. Structure of a Conclusion (15 mins)
A good conclusion has three parts:
- Claim: The answer to your question. ("Year 8 students prefer rugby over soccer.")
- Evidence: The numbers backing it up. ("My data shows 15 students chose rugby, while only 5 chose soccer.")
- Meaning: What does this mean in context? ("This suggests rugby is the dominant sport culture in our class.")
3. Task: Draft your Conclusion (20 mins)
Write your conclusion paragraph.
Checklist:
- Did I mention specific numbers?
- Did I answer my specific I-V-G question?
- Is it true based on my data?
4. Evaluation (5 mins)
Reflection: What could you have done better?
- "My sample size was too small."
- "My question was confusing."
- "I only asked my friends."
Identifying limitations is part of good statistical practice!
📋 Teacher Planning Snapshot
Ngā Whāinga Ako — Learning Intentions
Competing conclusions are drawn from the same shared data and settled on the evidence.
Ngā Paearu Angitū — Success Criteria
- ✅ I can distinguish what data shows from what it merely suggests.
- ✅ I can name the evidence that would settle a disagreement between two conclusions.
Differentiation & Inclusion
Scaffold support: Two written conclusions from the same data, one overreaching. Extension: identify the exact sentence where the overreach happens.
ELL / ESOL: Rehearse 'the data shows… the data suggests… the data cannot tell us…' as three distinct moves.
Inclusion: Ākonga may present their judgement in writing rather than aloud.
Mātauranga Māori lens: Both statistical reasoning and mātauranga hold that one season's observation does not settle a pattern. Say what yours cannot establish.
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
This lesson develops the Level 4 statistical-investigation objective through a real stage of the PPDAC cycle. See the unit curriculum companion for the exact source statement and lesson-to-evidence map.