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!