KS3 · Computer Science

Collecting and recording data

Your class votes on a new club. One tick gets typed in wrong — and the winner changes. Good data starts long before the typing: with a question.

Computer Science · Data

Same things. Two different questions.

Pick an item, then pick the box it belongs in. Read the reason every time — that's where the learning is.

Is this just raw values, or has it been given structure or meaning?

Still to sort

Data (0)

Raw values and facts, with no meaning given to them yet.

Where the line is: Data becomes information once it is given structure or meaning — headings, units, an organised table, a sentence saying what it shows.

Information (0)

Data that has been given structure or meaning, so it tells you something.

Where the line is: Being tidy isn't enough on its own: information has to tell you what the values mean.

7 of 7 still to sort.

Sort each item, then switch the question and sort the very same items again. Watch how an item's answer to one question tells you nothing about its answer to the other.

Watch out: Don't let one answer leak into the other. ‘I collected it myself’ doesn't make something data, and ‘it's in a neat table’ doesn't make it secondary.

Same question, asked two ways

Open question: ‘Which new club would you like?’ (write your answer)vsClosed question: ‘Which new club would you like? Tick one: Coding / Drama / Chess’

Your class wants to know which new club to start. Look at what each version of the question gives you back.

Focus

What comes back

Open question: ‘Which new club would you like?’ (write your answer)

‘coding’, ‘Coding club’, ‘codeing’, ‘computer coding’ …

Closed question: ‘Which new club would you like? Tick one: Coding / Drama / Chess’

Coding, Coding, Drama, Chess … always one of the three choices

The insight

Four people all wanted the same thing — but on the left a computer sees four different answers.

Recording it in a table

Open question: ‘Which new club would you like?’ (write your answer)

Someone has to decide what each answer means before typing it in

Closed question: ‘Which new club would you like? Tick one: Coding / Drama / Chess’

Each tick goes into the table exactly as it is

Counting the answers

Open question: ‘Which new club would you like?’ (write your answer)

‘coding’ and ‘codeing’ get counted separately unless you tidy them up first

Closed question: ‘Which new club would you like? Tick one: Coding / Drama / Chess’

Count how many times each choice appears — done

Computer Science · Recording data

Build the recording table

Your class wants to answer: ‘How does each of us get to school, and how long does it take?’ Set up a table to record the answers accurately.

Start from the question: for every student we need their travel method and their journey time.The question tells you exactly which data to collect — nothing more, nothing less.
missing step

Which line is step 2?

Give each student their own row — one row is one record.Give each travel method its own row, and list the students who use it.Write all the answers in one long row, left to right.

Computer Science · Checking data

Find the line where the data goes wrong

Your class votes on a new club using paper forms with tick boxes. One student types the forms into a table and works out the result. Which line is wrong?

One student's record of the vote — which line goes wrong?

Question: which new club do most of us want — Coding, Drama or Chess? Each of the 28 students ticks one box.
The forms are typed into a table: one row per student, with the columns Name and Club.
Check: the table has 28 rows — one per student, so nobody is missing and nobody is entered twice.
Row 16 — Leo's form: Chess ticked. Typed in: Chess.
Row 17 — Mia's form: Coding ticked. Typed in: Drama.
Counting the Club column: Coding 9, Drama 10, Chess 9.
Conclusion: Drama is the most popular, so the class should ask for a Drama club.

Computer Science · Collecting data

Put the whole job in order

The order you do these in when you collect data for a purpose

1 · First5 · Last

Record the answers in a table with clear headings
Choose how to collect it: survey, observation or measurement
Check the finished data for mistakes
Decide what question the data must answer
Decide which data you need and who to collect it from

Watch out: The tempting start is ‘just start collecting’. Without a question, you can't know which data you need.

Computer Science · Secondary data

Can you trust data you found?

You want to find out whether your town gets more rain in summer or in winter. You find a neat table of monthly rainfall figures on a website. You didn't collect it — someone else did, so it's secondary data.

Can you just go ahead and use it? Which is closest to what you think?

Yes — if it's been published online, someone must have checked it.Yes — it's organised in a proper table with headings, so it must be reliable.No — you should only ever use data you collected yourself.Not yet — first I'd check who collected it, when, and why.

How sure are you?

I'm sureI think soI'm guessing

Yes — if it's been published online, someone must have checked it.

This is a common misconception

Being published only means someone put it there. Nobody has promised you it's accurate. Before you use it, find out who collected it, when and why.

Yes — it's organised in a proper table with headings, so it must be reliable.

This is a common misconception

Headings and structure turn data into information, but they don't make it trustworthy. A neat table can still be out of date or collected for a one-sided reason. Check who collected it, when and why.

No — you should only ever use data you collected yourself.

This is a common misconception

Secondary data can be really useful: you could never measure years of rainfall yourself. The rule isn't ‘never use it’ — it's ‘check it before you use it’.

Not yet — first I'd check who collected it, when, and why.

This matches the evidence

Exactly. Who collected it tells you whose data you're relying on. When tells you whether it's recent enough for your question. Why tells you what it was collected for, which can shape what was collected. Then decide whether to use it.

Secondary data isn't trustworthy just because it's published or neat. Ask three questions first: who collected it, when, and why?

WHAT YOU'VE LEARNED

A quick recap of today's lesson.

Good data starts with a question. Know what you need to find out, and everything else — collecting it, recording it, checking it — follows from that.

What you need to know

Data is raw values and facts with no meaning given to them yet. Information is data that has been given structure or meaning, so it tells you something.
Primary data is data you collect yourself; secondary data is data somebody else collected. This is a separate question from data versus information.
Decide first what question the data must answer — that tells you which data to collect and who to collect it from.
Primary data can be collected with surveys or questionnaires, observations and measurements, including readings taken automatically by sensors. Secondary data comes from existing sources such as published data sets.
Record data in a consistent table and check it as it's entered and afterwards. Check secondary data for who collected it, when and why before you use it.

The big picture

Data is raw values with no meaning yet; information is data given structure or meaning. Separately, data you collect yourself is primary and data someone else collected is secondary. Collecting data for a purpose starts with the question it must answer. Record it consistently — one record per row, one field per column, clear headings, matching formats, fixed answer choices — and check it as it's entered and afterwards, because conclusions from inaccurate data can be wrong. Before using secondary data, check who collected it, when and why.

Key points

1Data = raw values and facts. Information = data given structure or meaning.

2Primary = you collected it. Secondary = somebody else collected it.

3Every item has an answer to both questions, and one answer doesn't tell you the other.

4Start with the question the data must answer.

5One record per row, one field per column, a clear heading on every column.

6Same format and units all the way down a column; fixed answer choices where possible.

7Typing mistakes, missing values, duplicates and out-of-range values make data inaccurate — and conclusions from inaccurate data can be wrong.

8Secondary data: check who collected it, when and why.

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Worked example

Problem

The PE department wants to know whether students in Years 7 to 9 would use a new lunchtime running club. Plan how to collect and record the data so it can be trusted.

⚠ Watch out

Mixing up the two questions: thinking anything you collected must be ‘data’ and anything from someone else must be ‘information’. ‘Data or information?’ asks whether it has meaning yet; ‘primary or secondary?’ asks who collected it. Your own neat table of results is primary information.

🧠

Memory hook

Question first, table second, check third. And for anyone else's data: Who? When? Why?

✓

Check yourself

A friend gives you their own neatly headed table of the class's heights. Data or information? Primary or secondary for you? (Information — the headings give it meaning. Secondary — your friend collected it.)

Flashcards

(15)

What is data?

Raw values and facts with no meaning given to them yet — for example, a list like 3, 7, 7, 12 with no headings.

What is information?

Data that has been given structure or meaning, so it tells you something.

What is primary data?

Data you collect yourself.

What is secondary data?

Data that somebody else collected, such as a published data set.

Are ‘data or information?’ and ‘primary or secondary?’ the same question?

No. The first asks whether it has been given meaning; the second asks who collected it. Every item has an answer to both.

What should you decide before collecting any data?

The question the data must answer. It tells you which data to collect and who to collect it from.

Name three ways of collecting primary data.

Surveys or questionnaires, observations, and measurements — including readings taken automatically by sensors.

In a recording table, what is a record?

One item — for example one student — stored in one row.

In a recording table, what is a field?

One kind of value, stored in one column with a clear heading.

Why should every value in a column use the same format and units?

Mixed formats like ‘60’ and ‘1 hr’ are easy to misread and hard to compare. Matching formats keep the data accurate and easy to analyse.

Why are closed questions easier to record than free text?

Everyone picks from the same fixed choices, so answers match exactly. Free text gets spelt and phrased in different ways.

Name four kinds of error that make data inaccurate.

Typing mistakes, missing values, duplicated entries, and values outside a sensible range.

Why does one wrong value in a table matter?

Conclusions drawn from inaccurate data can be wrong — one mistyped vote can change which choice comes out on top.

When should you check data for errors?

As it is entered, and again afterwards.

What three things should you check before using secondary data?

Who collected it, when, and why.

Tap any card to flip it, or use Study as deck to go through them one at a time. In the full lesson these run as a spaced-repetition deck — you rate each card Hard, Good or Easy and the tricky ones keep coming back until they stick.

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Same things. Two different questions.

Build the recording table

Find the line where the data goes wrong

Put the whole job in order

Can you trust data you found?

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