Community Data Inquiry Studio · Lesson 2: Posing Good Questions

Learning how to ask investigative questions that can be answered with data.

Community Data Inquiry Studio · Lesson 2

Studio checkpoint: refine the project question

Teams test whether their proposed question names a clear group, variable, and comparison or summary purpose. Peer consultants return the question with one strength, one ambiguity, and one practical collection risk.

Other teaching approach: Statistical Reasoning Seminar →

🎯 Learning Intentions

  • Understand the difference between a survey question and an investigative question
  • Learn the criteria for a good investigative question
  • Practise writing summary and comparison questions

🎥 Media Anchor (8 mins)

Video: Research Skills for Students

  • How can we rewrite a broad question so it becomes measurable?
  • What bias risk appears when a question is leading or vague?

1. Warm Up: Question Sort (10 mins)

Activity: Sort these questions into "Can answer with data" vs "Hard to answer with data":

  • "Who is the best rugby player?" (Subjective)
  • "How tall are the students in Room 5?" (Measurable)
  • "Why is blue the best colour?" (Opinion)
  • "What is the most common eye colour in our whānau?" (Countable)

2. Concept: Anatomy of a Question (15 mins)

A good investigative question needs I-V-G:

  • Interest: What property are you interested in? (e.g., height, lunch type)
  • Variable: What are you measuring? (e.g., centimetres, food category)
  • Group: Who are you measuring? (e.g., Year 8 students in Room 5)

Example: "What are the heights (V) of Year 8 students in Room 5 (G)?"

3. Activity: Fix the Question (20 mins)

Task: Turn these bad questions into good investigative questions:

  1. "Do you like sports?" → "primary sport played by Year 8 students"
  2. "Are we tall?" → "heights of students in our class compared to..."
  3. "Is this lunch healthy?" → "sugar content in lunchbox items of..."

4. Investigation Setup (10 mins)

Start thinking about your own investigation project. What are you curious about?

Draft 3 potential investigative questions for your project.

← Previous Lesson Next Lesson: Planning →

📋 Teacher Planning Snapshot

Ngā Whāinga Ako — Learning Intentions

Ākonga sharpen a vague question into one that names a variable and a group to compare.

Ngā Paearu Angitū — Success Criteria

  • ✅ I can write a question that names what is measured and which groups are compared.
  • ✅ I can state one question my data will NOT be able to answer, and why.

Differentiation & Inclusion

Scaffold support: Question stems that force a variable and a group: 'How does ___ differ between ___ and ___?' Extension: write a question your data could NOT answer, and say why.

ELL / ESOL: Rehearse the question aloud in pairs before writing; a question that cannot be said clearly cannot be investigated.

Inclusion: A question about the ākonga's own community is more accessible than a supplied one, and produces better statistics.

Mātauranga Māori lens: Iwi environmental monitoring starts from a question a community actually needs answered — kaimoana numbers, water quality. Ask ākonga who would use their answer.

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.