Session 2 — Asking Good Questions Grade 3 Data Science · Ages 8–9 ← → or Space · F = fullscreen
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Session 2 of 8

Asking Good
Questions

Not all questions can be answered with data. Today we learn which ones can — and how to write them well.

📊 Data Science for Young Minds · Grade 3
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Today's Plan

What We're Doing Today

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Warm-Up

Remember Session 1?

You went home and observed something carefully.

"What did you notice? Did you find a pattern?"

2–3 volunteers share. Then: "Now what if we wanted to turn your observations into a question — one we could actually investigate with data?"

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Lesson 1

What Can Data Answer?

Data questions are about things you can count, measure, or observe.

✅ Data CAN answer

  • How many students walk to school?
  • What is the most popular color?
  • How long does it take to read 10 pages?
  • Which fruit do most kids pick at lunch?

❌ Data CANNOT answer

  • What is the best movie ever?
  • Is math fun?
  • Why is the sky beautiful?
  • Should we have longer recess?
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Lesson 1

Turning Opinions into Data Questions

You can almost always rewrite an opinion question into a data question!

❌ Opinion question
"What is the best pizza topping?"
→
✅ Data question
"What pizza topping do MOST students in our class prefer?"
❌ Opinion question
"Is our school great?"
→
✅ Data question
"How many students would rate our school as great, okay, or needs improvement?"
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Lesson 2

Fair Questions vs. Biased Questions

A biased (leading) question pushes people toward one answer. A fair question gives everyone equal options.

❌ Biased — pushes you to say yes
"Don't you love reading books?"
✅ Fair — all options equal
"How much do you enjoy reading: love it, it's okay, or not for me?"
❌ Biased — guilt trips the answer
"You do eat vegetables every day, right?"
✅ Fair
"How many days per week do you eat vegetables: 0–2, 3–5, or every day?"
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Lesson 2

Open vs. Closed Questions

🔓 Open Questions

People answer freely — any answer goes

  • "What is your favorite subject and why?"
  • Gives rich, detailed answers
  • Harder to count and graph
  • Good for exploring ideas

🔒 Closed Questions

Pick from set choices only

  • "Which subject do you like best: Math, Reading, or Science?"
  • Easy to count and graph
  • Less detail
  • Good for collecting data

For data collection — closed questions are usually easier to work with.

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Activity!

Question Sort Challenge 🃏

Your group has 20 question cards. Sort them into two piles:

✅ Data CAN
answer this

❌ Data CANNOT
answer this

⏱ 12 minutes. If your group disagrees — great! That means you're thinking like data scientists. Be ready to explain your reasoning.

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🙋
Quick Vote — Hands Up!

Your teacher will read a question.
Thumbs UP = data can answer it.
Thumbs DOWN = data cannot.

Then explain your reasoning!

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Lesson 3

Who You Ask Matters

A sample is the group of people you ask. The people in your sample can change your results completely.

🚨 Biased sample example: You want to know the favorite sport of all 3rd graders. You only ask the soccer team. What will happen to your results?

✅ Fair sample: Ask students from different classes, different groups — a mix that represents everyone.

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Lesson 3

Sample Size Matters Too

How MANY people you ask affects how reliable your results are.

3 people asked Very unreliable — could be random
15 people asked Better — starting to see patterns
30 people asked Good — more trustworthy results

For class surveys — aim for at least 10–15 people. More is better!

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Activity

Fix the Bad Questions ✏️

Can you rewrite these questions to make them fair, specific, and data-ready?

Fix this ❌
"Don't you think homework is too much?"
Fix this ❌
"What is the best lunch?"
Fix this ❌
"You like dogs more than cats, right?"

📝 Use your worksheet Part 3. Work with a partner.

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Design Your Question

Your Data Question

Think of something you're genuinely curious about in your class or school.

Write a question that:
✅ Data can answer
✅ Is fair (not biased)
✅ You could actually ask classmates
✅ Has clear answer choices

📝 Part 4 of your worksheet. You'll use this question in Session 3 to actually collect data!

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Vocabulary Review

Words to Know

Data question
Answerable by counting, measuring, or observing
Biased question
Pushes toward one answer — unfair
Open question
Any answer is allowed
Closed question
Pick from set choices
Sample
The group of people you ask
Biased sample
Only asking certain groups — unfair
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Wrap Up

Session 2 Complete! 🎉

🔮 Coming up — Session 3: We take your question and actually collect the data using surveys, observation, and tally marks!