Best for
Week 5 synthesis after students have explored climate data, local impacts, traditional indicators, probability, and prediction quality separately.
Science + mathematics + mātauranga Māori • Years 7-10 • Unit 9 Week 5 synthesis
Unit 9 Week 5 Integrated Forecasting
Use this worksheet to make one forecast using multiple signals. Students combine scientific data, local observation, and ngā tohu o te taiao to produce a forecast, explain their confidence, and decide what should happen next.
Free synthesis task, premium local-forecast version
This version is ready to teach immediately. Te Wānanga becomes useful when you want iwi-specific indicators, local science datasets, or a more structured forecast template for your own context.
- Generate a scaffolded version for mixed-confidence classes.
- Swap in local tohu, whānau observations, or council monitoring data.
- Save an adapted Unit 9 forecasting pack in My Kete.
Kaiako planning snapshot
- Use length: 35-45 minutes.
- Grouping: Pairs for evidence gathering, individual final forecast.
- Prep: Provide or revisit at least one science dataset and one local or mātauranga Māori observation source.
- Teaching move: Ask students which signal changes the forecast most and why.
- Support / stretch: Offer a pre-filled signal row for support; ask students to write a confidence range and contingency action for stretch.
Resources already provided
- Signal-comparison table
- Confidence and tension prompts
- Final forecast and action-planning scaffold
- Dual-knowledge reflection prompt
- Teacher-only curriculum companion
This rebuild turns the old generic page into a real synthesis task across science, mathematics, and mātauranga Māori.
Ngā Whāinga Ako / Learning Intentions
- We are learning to combine different kinds of environmental evidence in one forecast.
- We are learning to explain confidence and uncertainty clearly.
- We are learning to use both science and mātauranga Māori respectfully when making decisions.
Paearu Angitu / Success Criteria
- I can identify more than one useful environmental signal.
- I can explain why some signals deserve more weight than others.
- I can make a forecast and describe what action should follow.
Curriculum integration / Te Mātaiaho alignment
The companion page makes the fit explicit around using ngā tohu o te taiao, ecosystem observation, and evidence communication to support defensible forecasting.
Strong forecasts come from more than one way of noticing
Scientific data can show patterns over time. Local observation and ngā tohu o te taiao can reveal place-specific changes that a graph might miss. Integrated forecasting asks students to use both responsibly.
This also keeps kaitiakitanga visible: if a forecast affects taiao or community wellbeing, the decision should be cautious, justified, and grounded in care for place.
1. Gather the signals
Record the evidence sources you will use in your forecast.
| Signal source | What does it suggest? | How confident are you? | Why does it matter? |
|---|---|---|---|
| Science dataset or graph | |||
| Local observation or field note | |||
| Ngā tohu o te taiao or maramataka-related signal |
2. Weigh the evidence
Strongest science signal
Which measurement or dataset carries the most weight?
Strongest local or Māori signal
Which observation or tohu adds the most useful insight?
Tension or disagreement
Where do the signals point in slightly different directions?
Extra evidence needed
What would help resolve the uncertainty?
3. Make the forecast
Forecast statement
What do you predict will happen next?
Confidence level
How confident are you, and why?
Action or preparation
What should people do now because of this forecast?
When will you check it?
What evidence will tell you whether the forecast was right?
4. Final reflection
Why is an integrated forecast stronger than using only one graph, one dataset, or one observation by itself?
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
Integrated forecasting has deep roots in mātauranga Māori. A skilled tohunga kōrero did not make environmental predictions from a single source — they wove together lunar phase, wind direction, species behaviour, ocean temperature, and accumulated seasonal memory into a single, contextualised judgement. That judgement carried weight because it was grounded in relationship: this person knew this place, and this place's patterns, intimately. Modern ensemble forecasting methods in climate science do something structurally similar — they combine multiple models and data sources to reduce uncertainty.
As you integrate your evidence sources today, hold both ways of knowing with respect. The scientific dataset gives you precision; the mātauranga Māori observation gives you place-specificity and long temporal depth. A forecast that accounts for both is stronger than one that uses either alone. Kaitiakitanga demands that forecasts serve the wellbeing of the taiao — which means they must be honest about uncertainty, cautious when evidence is mixed, and always oriented toward care for what comes next.
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