Best for
Week 2 data task — after field sampling or council data collection. Use alongside the Maramataka Creation handout to compare scientific and mātauranga Māori seasonal patterns.
Environmental Mātauranga • Unit 9 Week 2 • Years 7–10 • Data + Analysis
Seasonal Data Analysis
Record and graph seasonal environmental data, then interpret the patterns — connecting scientific measurements with maramataka-based knowledge of how the taiao changes across the year.
Free framework, premium localisation path
Want this pre-loaded with data from your local NIWA station or council monitoring programme? Te Wānanga can build a localised version with real regional data for your rohe.
- Pre-populate with local NIWA or council environmental monitoring data.
- Add mātauranga Māori seasonal indicators specific to your rohe and iwi.
- Save student data tables in My Kete for longitudinal comparison across the unit.
Kaiako planning snapshot
- Use length: 40–50 minutes. Data entry (~10 min), graphing (~20 min), interpretation + maramataka comparison (~15 min).
- Grouping: Pairs for data entry and graphing; individual for interpretation questions. Whole-class debrief to compare graphs across groups.
- Prep: Source local seasonal data in advance — NIWA CliFlo, council water quality monitoring, or school weather station logs. Rulers and graph paper, or a digital spreadsheet tool, both work fine.
- Differentiation: Entry: provide a partially completed graph with axes and scale already set up. On-level: students set up their own axes independently. Extension: plot two variables for a dual comparison and analyse any correlation.
- Neurodiversity support: Pre-printed graph grid helps students who find blank space overwhelming. Digital graphing tools are an equally valid alternative. Label key graph features together as a class before releasing to independent work.
Resources already provided
- Data recording table — season/date, variable, value + units, source, maramataka tohu
- Graph canvas with axis and title labelling prompts
- Five structured interpretation questions
- Maramataka connection prompt
- Entry / on-level / extension pathway
Local seasonal data must be sourced by the teacher or drawn from student field sampling. The handout structure works with any continuous environmental variable: temperature, rainfall, stream flow, turbidity, or species count.
Ngā Whāinga Akoranga / Learning Intentions
- We are learning to represent continuous environmental data accurately in a graph, with correctly labelled axes, scale, and title.
- We are learning to interpret patterns in environmental data — identifying trends, explaining causes, and recognising limitations.
- We are learning to connect scientific seasonal data with maramataka-based mātauranga Māori knowledge of the taiao.
Paearu Angitu / Success Criteria
- I can create a correctly labelled graph that accurately represents my seasonal data, with appropriate scale and title.
- I can describe a trend in my data using specific values from the graph — not just general observations.
- I can connect at least one pattern in the scientific data to a maramataka or mātauranga Māori seasonal observation.
Curriculum alignment / Te Marautanga o Aotearoa
This task connects to the NZ Curriculum Statistics strand (collecting, displaying, and interpreting data) and the Living World strand (environmental change and ecosystem dynamics). The maramataka connection integrates mātauranga Māori as a knowledge system across learning areas, in line with Te Marautanga o Aotearoa and the NZ Curriculum's principles of cultural diversity and inclusion.
Curriculum companion in progress
Why this matters in Aotearoa
The maramataka is a Māori lunar calendar that tracks environmental, seasonal, and celestial patterns — not to predict the weather in the Western sense, but to understand the rhythms of the taiao and know when to fish, plant, harvest, and rest. Kaitiaki who maintain maramataka knowledge can read seasonal change in ways that complement and sometimes exceed what instruments alone can capture. When ākonga place scientific seasonal data alongside maramataka knowledge, they practise the kind of knowledge dialogue that is at the heart of genuine environmental guardianship in Aotearoa.
Tuhituhinga raraunga / Data recording table
Record your environmental variable across at least four seasonal data points. Include the source and any maramataka observations for that season.
| Wā / Season or date | Variable measured | Value + units | Source | Maramataka tohu |
|---|---|---|---|---|
Maramataka tohu = seasonal environmental signs from mātauranga Māori relevant to this time of year (e.g. kōwhai flowering, kārearea behaviour, kōura spawning)
Kauwhata / Graph
Label your axes, add units, set your scale, give your graph a title, then plot your data.
y-axis label + units
x-axis label + units
Graph title and type (e.g. line graph of water temperature vs season):
Whakamāoritanga / Interpretation
What trend do you see? Describe it using specific values from your graph.
What might explain this seasonal pattern? Give at least two possible reasons.
What is one limitation of this data? (How it was collected, number of data points, what it doesn't measure.)
How does a maramataka tohu from your table connect to or contrast with your scientific data?
What would you collect or measure next to improve this analysis?
Entry, on-level, and extension pathway
Entry
Use a teacher-provided dataset and pre-drawn graph axes. Describe one trend and give one possible explanation. Skip the maramataka comparison column.
On-level
Set up your own graph axes. Complete all five interpretation questions. Connect the data to at least one maramataka tohu.
Extension
Plot two variables on the same graph and analyse correlation. Research whether local iwi maintain seasonal monitoring records and compare patterns with your scientific data.
Hononga Marautanga · Curriculum Alignment
Social Sciences — Ecological Sustainability
Level 3–4: investigate local environmental issues; understand that communities have responsibilities to protect the environment for future generations; develop the skills to take informed, responsible action.
Science — Living World / Planet Earth
Level 3–4: observe and describe patterns in the local environment; connect scientific observation to environmental decision-making; understand that human activity affects ecosystems and that this impact can be reduced through careful stewardship.
Aronga Mātauranga Māori
Mātauranga Māori encodes environmental knowledge in whakataukī — proverbs that carry ecological wisdom in compressed, memorable form. Sayings about the behaviour of kererū (NZ pigeon) in pōhutukawa flowering season, or the arrival of kōwhai blooms as a signal for planting, reflect generations of careful seasonal observation. This knowledge was not static: it was tested and updated across generations, much as a scientist updates a model when new data arrive.
The seasonal data analysis you are completing today is grounded in the same question that drove maramataka: what patterns repeat, which ones predict what comes next, and what do those patterns mean for how we act? As you analyse your data, look for patterns that confirm what mātauranga Māori already knew — and for any patterns that suggest recent environmental change has disrupted those traditional indicators.