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Session 1 of 8
Data Is
Everywhere
Today we start thinking like Data Detectives — beginning with the data that's already all around you.
🔍 Data Science for Young Minds · Grade 5 — Data Detective
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Today's Plan
What We're Doing Today
- 🎯 Hook — your apps and what they know about you
- 📊 Types of data: primary vs. secondary
- 🔢 Quantitative vs. qualitative data
- 🗂️ Structured vs. unstructured data
- 🕵️ Data Audit — mapping your personal data trail
- ✍️ Reflection — who collects your data and why?
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Opening Hook
Name 5 Apps You Used This Week
Think about yesterday. What apps or websites did you open?
For each app — what information does it need from you to work? What does it record about you?
Maps needs your location. Streaming apps remember what you watch. Games track your score and how long you play. Every app leaves a trail.
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Lesson 1
Your Data Trail
Every time you use technology, you leave a data trail — even without filling out a form.
At School
Attendance · Grades · Lunch choice · Library books · Test scores
On Devices
Search history · App usage · Location · Screen time · Messages
Health & Activity
Nurse records · Vaccinations · Fitness data · Sleep patterns
Most of this data was collected without you actively choosing to share it. That's worth thinking about.
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Lesson 2
Primary vs. Secondary Data
Primary Data — You Collect It
- You survey your classmates about favorite sports
- You measure rainfall in the schoolyard for a week
- You count how many cars pass in 10 minutes
Secondary Data — Someone Else Collected It
- You use census data from the government
- You read a published study on screen time
- You look up historical weather data online
Both types are valuable — but secondary data comes with questions: when was it collected? by whom? for what purpose?
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Lesson 2
Quantitative vs. Qualitative
🔢 Quantitative (Numbers)
- Test score: 87/100
- Height: 152 cm
- Screen time: 3.5 hours
- Attendance: 18/20 days
Can be measured, counted, averaged, graphed.
💬 Qualitative (Words/Categories)
- Favorite subject: "science"
- Mood today: "anxious"
- Lunch preference: "vegetarian"
- Comment: "great effort shown"
Can be sorted, themed, counted by category.
Most real datasets contain both types. A school record has your grade (quantitative) AND teacher comments (qualitative).
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Lesson 2
Structured vs. Unstructured Data
📋 Structured
- Organized in rows and columns
- Easy to sort, filter, analyze
- Spreadsheets, databases, grade books
- Example: student name | grade | attendance
📂 Unstructured
- No fixed format — free-form
- Harder to analyze automatically
- Photos, emails, social media posts, audio
- Example: a paragraph about your day
About 80% of the world's data is unstructured. Turning it into something analyzable is one of the biggest challenges in data science today.
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Activity Time!
Personal Data Audit
You're going to map your own data trail for one school day.
- 🤝 Step 1 (8 min): With a partner — list every piece of data collected about you from when you woke up to when you went to bed
- 📋 Step 2 (5 min): Classify each item: primary or secondary? quantitative or qualitative?
- 🗣️ Step 3 (7 min): Class combines lists — what did you miss?
🎯 Goal: By the end, you should have at least 15 different data points collected about you in a single day. Most students find 25–30.
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🧠
Brain Break — Data Type Sort!
Your teacher will read out a data point. Stand up for QUANTITATIVE, stay seated for QUALITATIVE.
Examples: your shoe size · your favorite color · how many siblings you have · your opinion of math · the temperature outside today
You just classified real data types — that's what data analysts do every day!
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Lesson 3
Who Collects Your Data — and Why?
Schools
Legal records, funding, academic progress, safety
Apps & Tech Companies
Improve products, target advertising, understand behavior
Governments
Census, public health, planning services, law
Researchers
Advance knowledge, test hypotheses, publish findings
Businesses
Understand customers, increase sales, improve products
Healthcare
Track health trends, improve treatment, prevent disease
The same data can serve many purposes — some helpful, some commercial, some you might question.
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Lesson 3
Data in Daily Life — It's Everywhere
- 🏥 Health: Doctors use your data to spot patterns that indicate illness before symptoms appear
- ⚽ Sports: Teams track every player's movement, speed, and decision to optimize strategy
- 📰 News: Headlines about "a study found..." are always based on collected data
- 🗳️ Government: Population data shapes school budgets, road building, healthcare planning
- 🎵 Entertainment: Streaming services use your listening/watching data to recommend content
A Data Detective's first question is always: "Where did this data come from, and who collected it?"
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Debrief
Audit Results — What Did You Find?
"Which category had the most data points? Which surprised you most? Who do you think has access to each item?"
- How many data points did your pair list? Did the class total surprise you?
- Which data did you actively choose to share vs. data collected passively?
- Is there any data on your list that makes you uncomfortable? Why?
- Which collector do you trust most with your data? Least?
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Reflection
Your Written Reflection
"Which piece of data from your audit surprised you most?
Who collects it — and why do you think they collect it?"
✍️ 6 minutes of quiet writing. Use your worksheet — Part 4. Write at least 3 sentences. Name a specific data point and make an inference about its purpose.
This is evidence-based reasoning — the core skill we'll build all year.
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Vocabulary Check
Session 1 Key Terms
Primary Data
You collect it yourself, directly from the source
Secondary Data
Collected by someone else; you use their dataset
Quantitative
Expressed as numbers; can be measured or counted
Qualitative
Expressed as words or categories; describes quality
Structured Data
Organized in rows and columns; easy to analyze
Data Trail
Digital records you leave behind as you use technology
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Session Close
The Detective's First Rule
"Before you can question data, you have to notice it exists."
- ✅ You can distinguish primary from secondary data
- ✅ You can classify data as quantitative or qualitative
- ✅ You've mapped your own data trail
- ✅ You've started asking "who collects this, and why?"
Next session: How do data scientists ask the right questions? We'll learn to turn vague curiosity into testable hypotheses.