Best for
Week 5 after students have worked with more than one forecast or environmental prediction and need to judge reliability instead of accepting every prediction equally.
Mathematics + science • Years 7-10 • Unit 9 Week 5 evidence review
Unit 9 Week 5 Prediction Accuracy Analysis
Use this worksheet to compare environmental forecasts with what actually happened. Students measure how close predictions were, explain why some were stronger than others, and decide how future forecasts can better support local action.
Free forecast-review task, premium local-dataset version
This version is ready to teach immediately. Te Wānanga becomes useful when you want your own class weather logs, NIWA records, council data, or lower-reading comparison prompts inserted.
- Generate a simpler scaffold with fewer variables for support classes.
- Swap in a local dataset from your rohe or school monitoring project.
- Save an adapted Unit 9 evidence-review pack in My Kete.
Kaiako planning snapshot
- Use length: 30-40 minutes.
- Grouping: Pairs for comparison, individual judgement writing.
- Prep: Bring at least two predictions and the observed outcome for the same event or period.
- Teaching move: Push students beyond “right” or “wrong” into why a prediction succeeded, failed, or only partly worked.
- Support / stretch: Pre-fill one row for support; ask students to compare numerical and non-numerical forecasts for stretch.
Resources already provided
- Forecast versus outcome comparison table
- Error and reliability reflection prompts
- Improvement-planning cards
- Mātauranga Māori caution-and-care prompt
- Teacher-only curriculum companion
This rebuild turns the old generic graph page into a real evidence-quality task for environmental prediction.
Ngā Whāinga Ako / Learning Intentions
- We are learning to compare predictions with actual environmental outcomes.
- We are learning to explain why some forecasts are more reliable than others.
- We are learning to improve future predictions using evidence and careful judgement.
Paearu Angitu / Success Criteria
- I can compare at least two predictions with real outcomes.
- I can explain what made one forecast stronger or weaker.
- I can suggest one improvement for the next forecast.
Curriculum integration / Te Mātaiaho alignment
The companion page makes the mathematics fit explicit around time-series investigation, data communication, and evidence-based judgement rather than treating forecasting as guesswork.
Good forecasts are tested, not just trusted
A prediction becomes useful when students can compare it with what actually happened and explain the gap. That helps them decide whether a model, dataset, or observation should shape future action.
Through a mātauranga Māori lens, this also asks how kaitiakitanga shapes cautious decision making: if uncertainty is high, people still need to act carefully to protect taiao and community wellbeing.
1. Compare forecasts with outcomes
Complete the table using classroom, NIWA, local, or school-collected data.
| Forecast or prediction | What was predicted? | What actually happened? | How close was it? | What might explain the gap? |
|---|---|---|---|---|
| Temperature or heat forecast | ||||
| Rainfall or storm forecast | ||||
| River, soil, or ecosystem condition prediction |
2. Judge the accuracy
Most accurate prediction
Which prediction was closest to reality? What evidence proves that?
Least accurate prediction
Where was the biggest gap, and what may have been missed?
Confidence in the source
Which source would you trust most next time, and why?
Limitations
What data, time period, or local factor may have reduced accuracy?
3. Improve the next forecast
Extra evidence to collect
What would make the next prediction stronger?
Local observation
How could whānau knowledge, school observations, or ngā tohu o te taiao improve the forecast?
4. Final judgement
Write one sentence that explains how accurate the forecast set was overall and what should change before the next prediction is used for environmental action.
Ngā Whāinga Akoranga · Learning Intentions
- We are learning to use evidence from multiple sources to understand environmental change.
- We are learning to connect scientific data with mātauranga Māori observations of the taiao.
- We are learning to make informed, evidence-based decisions about environmental care.
Hononga Marautanga · Curriculum Alignment
Science — Planet Earth and Beyond
Level 3–4: investigate how the Earth's climate has changed over time; understand how human activity affects ecosystems and atmospheric systems; use evidence to evaluate claims about climate impacts on local environments and communities.
Social Sciences — Ecological Sustainability
Level 3–4: understand that environmental changes have consequences for communities and future generations; develop the ability to evaluate responses to environmental challenges and propose informed, responsible action.
Aronga Mātauranga Māori
In traditional Māori environmental knowledge, prediction was not a one-off event — it was a cycle of observation, forecast, action, and return. A tohunga kōrero who made a seasonal forecast would observe whether the signs they read proved accurate, and update their understanding accordingly. This iterative calibration process is exactly what prediction accuracy analysis formalises: make a claim, wait, measure the outcome, evaluate the claim, improve the model. The epistemological logic is the same across both knowledge systems.
As you assess prediction accuracy today, consider what counts as a 'correct' forecast. In mātauranga Māori, a forecast that led to appropriate kaitiakitanga action might be valued differently from one that was numerically precise but failed to prompt protective behaviour. In science, accuracy is measured against observed data. Both measures matter: an accurate forecast that no one acts on is no better than a rough estimate that provokes wise stewardship.
Ngā Rauemi Tautoko · Support Materials
Resources already provided:
- This handout — complete during Weeks 4–5 of the climate inquiry
- Traditional Climate Indicators (unit-9-week4-traditional-climate-indicators.html) — mātauranga Māori lens on environmental change signals
- Local Climate Impacts Worksheet (unit-9-week4-local-climate-impacts-worksheet.html) — evidence-based local impact analysis
- Integrated Forecasting (unit-9-week5-integrated-forecasting.html) — synthesis task combining scientific and mātauranga knowledge
- Probability Modeling (unit-9-week5-probability-modeling.html) — quantitative forecasting methods
- Prediction Accuracy Analysis (unit-9-week5-prediction-accuracy-analysis.html) — evaluate how accurate environmental forecasts were