Duration: 3 lessons (50 minutes each) | Year Level: 8
How do we use data to make decisions in Aotearoa?
Focus: Understanding how data is used in te ao MÄori and why it matters
PÅwhiri Data: Students share one piece of data about themselves (e.g., number of siblings, favourite subject) while standing in a circle. Teacher records responses on the board.
WhakatÅhea: "What stories do these numbers tell us about our class?"
Watch: "Data and Indigenous Communities" (5-minute video introduction)
Discussion Questions:
Te KÅhanga Reo movement tracks enrolment, language outcomes, and cultural engagement to demonstrate the success of MÄori-medium education. This data helps secure funding and support.
Students complete a Data Types Sorting Activity:
| Data Example | Categorical or Numerical? | Why? |
|---|---|---|
| Favourite kai (food) | Categorical | Can't be measured numerically |
| Height in centimeters | Numerical | Can be measured and counted |
| Number of people in whÄnau | Numerical | Counted as whole numbers |
| Iwi affiliation | Categorical | Names/categories, not numbers |
Focus: Collecting real class data and understanding variables
Data Detectives Warm-up: Students look around the classroom and identify 5 pieces of data they could collect (e.g., number of windows, types of stationery, hair colours).
Students work in pairs to collect data on three topics:
Question: "What's your favourite way to be active?"
Options: Rugby, Netball, Swimming, Cycling, Kapa Haka, Other
Data Type: Categorical
Question: "How many people live in your household?"
Range: 1-10+ people
Data Type: Numerical (discrete)
Question: "How long does it take you to get to school?"
Categories: 0-10 mins, 11-20 mins, 21-30 mins, 30+ mins
Data Type: Numerical (continuous - grouped)
Collection Method: Students create simple tally sheets and survey their classmates respectfully.
Pairs compile their data into class totals using a shared Google Sheet template.
Template includes: Student names (optional), responses for each question, totals and percentages.
Focus: Creating visual representations using digital tools
"Graph Gallery Walk": Display examples of bar graphs, pie charts, and dot plots. Students vote on which graph type best shows each data set.
Using Google Sheets: Students create three different graphs from their collected class data.
Success Criteria:
Pair-Share: Students explain to a partner which graph tells the "best story" about their class data and why.
Class Discussion:
Assessment Method: Quick online quiz (10 questions, 15 minutes)
Success Criteria:
"Kia kaha ki te kimi raraunga!"
Be strong in seeking data!
Students will develop statistical investigation skills ā tÅ«huratanga raraunga ā through authentic data contexts drawn from Aotearoa New Zealand. Using real datasets about MÄori communities, sport, environment, and society, students will learn to question, collect, analyse, and communicate statistical findings with cultural awareness and critical thinking.
Scaffold support: Provide pre-structured investigation templates and graph frameworks for entry-level learners. Offer extension tasks requiring students to conduct an independent investigation on a topic of their choice, including a written analysis and critical evaluation of their own statistical process.
ELL / ESOL: Pre-teach statistics vocabulary (mean, median, mode, range, sample, population). Use visual data displays and real-world datasets students can connect to personally. Allow oral explanation of statistical reasoning before written tasks.
Inclusion: Offer calculator and digital tools access to all learners. Neurodiverse learners benefit from structured inquiry cycles, visual data displays, and real-world data that provides motivating authentic context. Ensure graph-reading activities include both visual and tabular formats.
MÄtauranga MÄori lens: Connect tÅ«huratanga (statistical inquiry) to traditional MÄori practices of observation, pattern recognition, and knowledge-making through careful attention to the natural and social world. Use datasets about MÄori communities, land, or environmental trends ā with attention to the ethics of data sovereignty (who owns data about MÄori communities and how should it be used). The maramataka itself is a sophisticated data system encoding centuries of ecological observation.
Prior knowledge: Best used after foundational number and measurement skills. Builds on Year 7 statistics exposure.