GCSE · Geography · AQA · Spec 8035

Evaluation of geographical enquiry

A day by a river, a notebook full of pebble lengths, a conclusion you're proud of. Now the awkward bit: how much would you actually bet on it?

A hypothetical river enquiry

Would you bet on this conclusion?

The claim

A class asked: ‘Are the pebbles at Site B smaller than the pebbles at Site A?’ They concluded: yes, they are. Claim: this conclusion can be trusted.

Place each piece of evidence to load the balance. Mark the strong ones — they count double.

They measured Site A again, the same way, on two more days — and the mean pebble length came out very similar each time.
Evidence 1: does it support or challenge the claim?SupportsChallenges
Strong evidence
They measured pebble length at both sites — exactly what their question asked about.
Evidence 2: does it support or challenge the claim?SupportsChallenges
Strong evidence
They only measured a handful of pebbles at each site.
Evidence 3: does it support or challenge the claim?SupportsChallenges
Strong evidence
Nobody planned which pebbles to measure — people grabbed whichever were easiest to reach.
Evidence 4: does it support or challenge the claim?SupportsChallenges
Strong evidence
One person called out the lengths while another scribbled them down in a hurry.
Evidence 5: does it support or challenge the claim?SupportsChallenges
Strong evidence
It started to rain, so Site B was measured in a rush before the class had to leave.
Evidence 6: does it support or challenge the claim?SupportsChallenges
Strong evidence
The pebbles were only measured on the few days the class happened to visit.
Evidence 7: does it support or challenge the claim?SupportsChallenges
Strong evidence

Reliable vs valid

Reliable datavsValid data

Two words the balance leaned on. They sound alike and are easy to mix up, so here they are side by side. Tap each insight.

Focus

What it means

Reliable data

You'd get the same result if you collected it again on a comparably similar occasion.

Valid data

It lets you answer your enquiry question successfully.

The insight

This is the difference that matters most. Reliable is about repeating; valid is about answering. They're separate checks — data that comes out the same every time still has to be checked against the question.

The question to ask yourself

Reliable data

If I collected this again, would I get the same result?

Valid data

Does this data actually answer my question?

What it looks like

Reliable data

Sediment measured with the same method on different days gave mean lengths of 36 mm, 34 mm and 38 mm.

Valid data

Your question asks about pebble size, and your data measures pebble size.

Why it matters

Reliable data

Reliable data can be trusted to form a conclusion.

Valid data

Without valid data, the question can't be answered successfully.

Every stage counts

Which stage is this comment about?

Pick a comment from a hypothetical enquiry, then choose the stage it evaluates.

Still to sort

Data collection (0)

How the data was gathered.

Where the line is: About gathering the data in the first place — not what you did with it afterwards.

Data presentation (0)

How the results were shown.

Data analysis (0)

How the results were worked through.

Conclusion (0)

What the enquiry found, and what it added to your understanding.

Where the line is: About what the enquiry showed you — not about the methods used to get there.

6 of 6 still to sort.

Most of what you put on the balance came from how the data was collected. But a full evaluation looks back over the whole enquiry — not just the day out with the clipboard.

Watch out: Easy trap: piling every comment into ‘data collection’. A full evaluation reaches every stage.

The odd one out

One reading doesn't fit. Now what?

Hypothetical: you plot your readings and one value sits well away from the general trend of all the others.

Which is closest to what you'd do first?

It's clearly a mistake. Delete it so the results look tidy.Before blaming anyone, look for a real-world reason that reading might be different.Find out who misread the equipment — that'll explain it.It's the biggest number in my table, so that must be the anomaly.

How sure are you?

I'm sureI think soI'm guessing

It's clearly a mistake. Delete it so the results look tidy.

This is a common misconception

Tempting — but hold on. That value is an anomaly: a piece of data that sits outside the general trend. It might be a slip, but it might also have been collected in different conditions to the rest. Delete it now and you'll never find out which.

Before blaming anyone, look for a real-world reason that reading might be different.

This matches the evidence

Yes — this is how a geographer thinks. An anomaly may have been collected in different conditions, or come from human error in collecting and recording it, or from faulty equipment. But geographers don't automatically assume error. They look first for the real-world geographical variables that might have made that piece of data different.

Find out who misread the equipment — that'll explain it.

This is a common misconception

Human error and faulty equipment are both possible causes, so they're worth checking. But starting there means assuming error, and a geographer doesn't do that automatically. The first question is whether something real about the place made this reading different.

It's the biggest number in my table, so that must be the anomaly.

This is a common misconception

Not quite. An anomaly is a value outside the general trend — not simply the biggest one. A high value that follows the trend isn't an anomaly at all.

An anomaly is a clue before it's a mistake. Look for the geography first.

Predict, then check

Objective data is data considered to be factual. Subjective data is data based on opinions.

Two hypothetical studies of the same town centre. Study 1 collects mostly objective data. Study 2 collects mostly subjective data. Which study gives the more conclusive answer?

Your turn

Write it like a geographer

Hypothetical enquiry: a group planned to count pedestrians at five sites across a town centre. They ran out of time and only counted at two of the sites.

Evaluate one problem with the data collection in this enquiry. Say what the problem was, how it affected the results, and how it could be avoided in future. [3 marks]

Your answer

0 words · your answer stays on this page and is not sent anywhere.

The mark scheme

Names the problem: they ran out of time, so only two of the five planned sites were counted. (1 mark)
Says how it affected the results: they have less data than planned, covering only part of the town centre, so any conclusion is weaker. (1 mark)
Suggests a sensible way to avoid it next time that fits the problem, e.g. allowing more time or counting the remaining sites on another day. (1 mark)

Model answer

The main problem was time: the group ran out of it, so they only counted pedestrians at two of the five sites they had planned. This means they have less data than they intended, and it only covers part of the town centre, so any conclusion they draw about the whole centre is weaker. To avoid this in future, they could allow more time for the fieldwork, or come back on another day to count at the remaining three sites.

Problem → effect → how to avoid it. And notice what you just did: you wrote down a flaw in plain sight. That isn't a sign of a poor geographer. Good geographers present their findings honestly, even when they show errors that affect the outcome.

WHAT YOU'VE LEARNED

A quick recap of today's lesson.

Evaluating an enquiry isn't owning up to failure. It's weighing up what makes your conclusion strong, what makes it shaky, and saying so honestly.

What you need to know

Evaluate every stage of an enquiry — data collection, data presentation, data analysis and the conclusion — not just data collection.
At the data collection stage, reflect on the amount of data, whether the sampling strategy was appropriate, possible human error, and practical things like the weather and time available.
Reliable data gives the same result on a comparably similar occasion; valid data lets you answer your enquiry question. Both affect how strong your conclusion is.
Objective data is considered factual; subjective data is based on opinions. Mostly objective studies lose some tone and distinction; mostly subjective studies are less conclusive.
An anomaly sits outside the general trend. Look for a real-world geographical reason before assuming human or equipment error.
Data only captures a snapshot in time, so it never tells the whole story of a place.

The big picture

Evaluating a geographical enquiry means looking back over every stage — data collection, presentation, analysis and the conclusion — to judge how far the conclusion can be trusted. Reliable data gives the same result on a comparable occasion; valid data answers the enquiry question; together they decide how strong the conclusion is. Anomalies are investigated for a geographical cause before error is assumed, objective and subjective data each have a cost, and good geographers present flaws honestly and say how the study could be improved.

Key points

1Evaluation is a judgement about how far a conclusion can be trusted, not a list of what went wrong.

2Every stage gets evaluated: collection, presentation, analysis and conclusion.

3Reliable = same result on a comparable occasion. Valid = answers the question.

4When evaluating the conclusion, ask whether the enquiry let you see patterns and relationships you couldn't otherwise have seen.

5Good evaluation points name the problem, its effect on the results, and how it could be avoided in future.

6Good geographers suggest other data that would improve or extend the study, and present flaws honestly.

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Worked example

Problem

Hypothetical: a student's enquiry question is ‘Are the pebbles smaller at Site 2 than at Site 1?’ They measured the water temperature at both sites on three different days and got almost the same temperatures each time. Is this data reliable, valid, both or neither?

⚠ Watch out

Writing an ‘evaluation’ that only lists what went wrong on the day of data collection. A strong evaluation covers every stage and then uses those points to judge how far the conclusion can be trusted.

🧠

Memory hook

RE-liable = RE-peat it and get the same result. VALID = it answers the question you asked. Then weigh it up: every evaluation point either props your conclusion up or pulls it down.

✓

Check yourself

Cover the page. A friend says: ‘One reading didn't fit the pattern and it rained, so my enquiry's ruined — I'm leaving that out of my write-up.’ What two things would you tell them?

Flashcards

(14)

What is the evaluation stage of a geographical enquiry for?

Reflecting on the quality and appropriateness of the methods, techniques and approaches used, the quality of the data and how helpful it was to form a conclusion, and how the study could be improved and extended.

Which stages of an enquiry should be evaluated?

All of them: data collection, data presentation, data analysis and the conclusion — not just data collection.

Four things to reflect on when evaluating data collection

The amount of data collected, whether the sampling strategy was appropriate, whether human error affected the data, and practical considerations such as the weather or time available.

Reliable data

Data that would give the same result on a comparably similar occasion — so it can be trusted to form a conclusion.

Valid data

Data that allows the geographer to answer their enquiry question successfully.

Why evaluate how reliable and valid the data is?

Because reliability and validity affect the strength of the conclusions made.

Objective data vs subjective data

Objective data is considered to be factual. Subjective data is based on opinions.

The cost of a mostly objective study — and of a mostly subjective one

Mostly objective: loses some of the tone and distinction that makes the subject interesting. Mostly subjective: not as conclusive, because it relies only on personal viewpoints.

How could an enquiry whose data is all subjective be improved?

By gathering some more objective data if the enquiry were done again.

Anomaly

A piece of data that sits outside the general trend.

Possible reasons for an anomaly

It was collected in different conditions, human error in collecting or recording it, or faulty equipment. Look for real-world geographical variables first rather than assuming error.

Why will fieldwork data never tell the whole story of a place?

It only captures a quick snapshot in time, and it isn't collected with all possible variables and influences in mind.

A key question when evaluating the conclusion

Did the data, and the way it was presented and analysed, let me see patterns and relationships I couldn't otherwise have seen? That's the value the enquiry added.

Is pointing out flaws in your enquiry a sign of a poor geographer?

No. Good geographers present findings honestly and transparently, identify problems, explain how they affected the results and say how they could be avoided.

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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Would you bet on this conclusion?

Which stage is this comment about?

One reading doesn't fit. Now what?

Write it like a geographer

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