Computer Science · 9th Grade

Active learning ideas

Correlation vs. Causation

Active learning works for this topic because students need to experience the confusion between correlation and causation firsthand to truly grasp the difference. When they argue, graph, and analyze real examples, they move from abstract definitions to concrete understanding of why data literacy matters in everyday life.

• Common Core State Standards
• CSTA: 3A-DA-12

• 20–35 min
• Pairs → Whole Class
• 3 activities

Activity 01

• Formal Debate
• 25 min · Whole Class

Formal Debate: Does Ice Cream Cause Drowning?

Present the classic ice cream and drowning correlation (both rise in summer). Half the class argues it is causal; the other half argues against. After three minutes of debate, introduce the confounding variable (summer heat) and discuss what evidence would have been needed to establish causation.

Explain why correlation does not necessarily imply a causal relationship.

Facilitation Tip

For the Debate activity, assign roles as either 'correlation-only' or 'causation-possible' teams to force students to grapple with the limits of observational data.

What to look for

Provide students with three scenarios: one showing clear causation, one showing correlation without causation, and one with a potential confounding variable. Ask students to label each scenario and write one sentence explaining their reasoning for the correlation/causation distinction.

• Analyze
• Evaluate
• Create
• Self-Management
• Decision-Making

Activity 02

• Gallery Walk
• 35 min · Small Groups

Gallery Walk: Spurious Correlations

Post five or six real spurious correlation charts around the room. Groups rotate and for each chart write: (1) the apparent conclusion someone might draw, (2) why correlation does not prove causation here, and (3) a plausible confounding variable. Groups share their best find with the class.

Differentiate between correlation and causation using real-world examples.

Facilitation Tip

During the Gallery Walk, have students physically move to each graph and write a one-sentence claim about the relationship before moving on, ensuring all students engage with every example.

What to look for

Present students with a headline like 'Study Shows Coffee Drinkers Live Longer.' Ask them: 'What is the correlation being presented here? What are two possible confounding variables that could explain this correlation? What kind of study design would be needed to suggest causation?'

• Understand
• Apply
• Analyze
• Create
• Relationship Skills
• Social Awareness

Activity 03

• Think-Pair-Share
• 20 min · Pairs

Think-Pair-Share: News Headline Analysis

Provide four recent news headlines that imply causation from correlational data. Students individually identify the implied causal claim and whether the evidence supports it. Partners compare their analysis and discuss what a rigorous study would need to do differently.

Critique claims of causation based solely on correlational data.

Facilitation Tip

For the Think-Pair-Share, provide a mix of credible and questionable headlines so students practice identifying what additional information they need to evaluate causation claims.

What to look for

Show students two graphs: Graph A displays a strong positive correlation between two unrelated variables (e.g., number of pirates and global warming). Graph B displays a clear causal relationship (e.g., hours studied and test scores). Ask students to identify which graph represents correlation only and which might represent causation, and to briefly justify their answers.

• Understand
• Apply
• Analyze
• Self-Awareness
• Relationship Skills

A few notes on teaching this unit

Teach this topic by making students confront the limits of correlation before they learn about causation. Start with examples where correlation is clearly not causation to build skepticism, then introduce well-designed studies where causation is established. Avoid teaching the phrase 'correlation does not imply causation' too early—students need to feel its truth through experience. Research shows that students retain this distinction better when they actively debunk misleading claims rather than passively receive definitions.

Students will confidently distinguish between correlation and causation by the end of these activities. They should be able to spot spurious correlations, explain confounding variables, and critique misleading statistical claims with clear reasoning and evidence.

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Watch Out for These Misconceptions

• During Debate: Does Ice Cream Cause Drowning?, watch for students who claim that ice cream sales directly cause drowning because both increase in summer.

  Redirect these students to calculate the correlation coefficient and discuss what lurking variables (like temperature or pool usage) might explain the pattern, then have them revise their argument using evidence from the debate.

• During Gallery Walk: Spurious Correlations, watch for students who assume the strength of a correlation indicates causation.

  Stop them at graphs where variables are strongly correlated but logically unrelated (like the pirate and global warming example), and ask them to explain why high correlation alone doesn’t prove causation, using the visual evidence in front of them.

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Methods used in this brief

• Formal Debate
• Gallery Walk
• Think-Pair-Share