GCSE · Geography · AQA · Spec 8035

Reaching evidenced conclusions in fieldwork

A day on a beach with a tape measure only pays off if you can say what it means — without claiming one thing more than your data can carry.

Geography · Fieldwork conclusions

How much is standing behind each sentence?

Imagine your class measured the size of pebbles at sites running from the water's edge up to the top of a beach. Here are six sentences someone wants to put in the conclusion. Sort each one by how much evidence is really behind it.

Still to sort

Empirical evidence (0)

A factual statement that's hard to dispute, because it comes from direct observation.

Where the line is: You saw or measured it yourself. Once a sentence goes beyond what was actually recorded — a trend across the whole beach, say — it is no longer empirical evidence.

Interpretation (0)

A statement the data strongly points towards being true.

Where the line is: The data points to it, even though you didn't observe every case. That's what separates it from an assumption, where your data doesn't test the claim at all.

Assumption (0)

A statement you assume to be true.

Where the line is: It might well be right — but nothing you collected tests it. Collect data that does test it, and it can become an interpretation.

False conclusion (0)

A statement with no evidence that it is true.

Where the line is: Nothing in your data backs it up. Some false conclusions even go against what the data shows.

6 of 6 still to sort.

This beach enquiry is made up so you can practise. The skill isn't: every fieldwork conclusion you ever write is made of statements like these.

Exam line: Build your conclusion from empirical evidence and interpretations. Leave assumptions and false conclusions out — or go and collect the data that tests them.

Watch out: A statement can sound perfectly sensible and still be an assumption. The question is never 'does this sound right?' — it's 'did my data actually test this?'

From numbers to a conclusion

Work through it in order. The trap is jumping straight to the conclusion before you've described what the data actually shows.

D — Data quotationQuote individual pieces of the data to back up what you've said — for example, the size of the greatest change between two points.
Answer the enquiry questionNow — and only now — write the conclusion. It exists to answer your enquiry question, so answer it directly, using what your description has shown.

Analysing words, not numbers

CodingvsDiscourse analysis

Two methods for qualitative data. The key difference is the question each one asks of the source.

Focus

The question it asks

Coding

What areas of thought or opinion come up — and where?

Discourse analysis

How and why was this written this way — not only what does it say?

The insight

Keep this difference sharp. Coding tracks WHAT people think; discourse analysis looks at HOW and WHY a resource was put together.

Used on

Coding

Interviews and questionnaires

Discourse analysis

Articles, social media posts, adverts and blogs

What you actually do

Coding

Create a code for each area of thought — e.g. soc+ for a positive social impact, env- for a negative environmental impact, econ- for a negative economic impact — and mark where each one comes up in a transcript.

Discourse analysis

Look at the structure and layout, the language used, the intended audience and when it was written.

What it's for

Coding

Finding patterns of thought between respondents

Discourse analysis

Understanding how and why the resource was written the way it was

Predict, then check

This is where over-claiming sneaks in. Commit to an answer before you look.

In a questionnaire, most respondents strongly agreed with this statement: 'Money has to be invested in flood defences if homes are to be protected.' Which conclusion does that result actually support?

Geography · Anomalies

The result that doesn't fit

Back on the beach. At one site near the top, the pebbles you measured were much smaller than at the sites either side — it sits well outside the general trend. It's also the opposite of what you expected to find there.

What should you do with that result? Pick the idea closest to what you'd honestly do.

Leave it out. It's obviously a mistake, and it spoils an otherwise clear pattern.Change the value so it fits the line of best fit — the pattern is clearly right.Put it down to human error or faulty equipment straight away, and move on.Keep it, and first look for a real geographical reason that could explain it.

How sure are you?

I'm sureI think soI'm guessing

Leave it out. It's obviously a mistake, and it spoils an otherwise clear pattern.

This is a common misconception

This feels tidy, but it's the classic trap. Keeping only the results that agree with what you already believed, and dropping the rest, is called confirmation bias: concluding what you already thought by using some, but not all, of the evidence. A good conclusion takes account of all the evidence — including the awkward bits.

Change the value so it fits the line of best fit — the pattern is clearly right.

This is a common misconception

Altering a result to fit the pattern is exactly what geographers avoid. The moment you do it, your conclusion is resting on data you invented rather than data you collected — and the result might have been telling you something real.

Put it down to human error or faulty equipment straight away, and move on.

This is a common misconception

An anomaly can come from different collection conditions, human error or faulty equipment — so these are fair possibilities. But they're not the first place to look. If you jump straight to 'error', you might throw away a genuine geographical finding.

Keep it, and first look for a real geographical reason that could explain it.

This matches the evidence

Exactly. An anomaly is data that sits outside the general trend, and it belongs in your conclusion. Geographers first look for a real-world geographical variable that could explain it. Different conditions, human error or faulty equipment are possibilities too — they're just not where you start.

An anomaly is something to explain, not something to delete. Take account of ALL the evidence — including the results you didn't expect.

Put it all together

Write a developed conclusion

Made-up findings for practice. (1) At most sites, pebbles got larger from the water's edge up to the top of the beach. (2) At one site near the top, the pebbles were much smaller than at the sites either side. (3) A second group repeated the whole survey on a similar day and found a very similar pattern. (4) Pebble size was measured at every site. (5) No data on waves was collected.

Use the findings below to write a conclusion to this enquiry question: 'To what extent does pebble size increase up the beach?' A simple yes/no question would only allow a simple conclusion — this one asks for a developed one, so weigh what supports the idea against what contradicts it, comment on how reliable and valid the data is, and say what you can and can't conclude about what causes the pattern. Data is reliable if the same result would be collected on a comparably similar occasion, and valid if it lets you answer the enquiry question. [6 marks]

Your answer

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

The mark scheme

Answers the enquiry question with a judgement of extent (e.g. 'to a large extent, but not completely') rather than a simple yes or no. (1 mark)
Uses the supporting evidence: pebbles got larger up the beach at most sites. (1 mark)
Weighs the contradictory evidence: the site near the top with much smaller pebbles is included and discussed, not ignored. (1 mark)
Judges the data reliable, because a repeat survey on a similar day found a very similar pattern. (1 mark)
Judges the data valid, because pebble size was measured at every site, which is what the question asks about. (1 mark)
States that waves causing the pattern cannot be concluded, because no wave data was collected (it stays an assumption). (1 mark)

Model answer

Pebble size increases up the beach to a large extent, but not completely. At most sites the pebbles got larger from the water's edge to the top of the beach, which supports the idea. However, at one site near the top the pebbles were much smaller than at the sites either side, so the increase is not perfectly consistent — and before treating that site as an error, I would first look for a real geographical reason that could explain it. The data is reliable, because a second group repeated the survey on a similar day and found a very similar pattern. It is also valid, because pebble size was measured at every site, which is exactly what the question asks about. I cannot conclude that waves cause the pattern, because no wave data was collected, so that remains an assumption.

A developed conclusion does four jobs: gives a judgement, backs it up, weighs what goes against it, and says how far the data can be trusted.

WHAT YOU'VE LEARNED

A quick recap of today's lesson.

Say exactly what your data shows — no less, and definitely no more.

What you need to know

A conclusion answers the enquiry question, using careful analysis of all the data you collected.
Describe the data before you conclude: GRaDE for numbers; coding or discourse analysis for words.
Build conclusions on empirical evidence and interpretations — never on assumptions, false conclusions or only the results you liked.

The big picture

A fieldwork conclusion answers your enquiry question using careful analysis of all the data you collected. Describe numbers first with GRaDE (General trend, Range, Data quotation, Exceptions) and add meaning with the mean, mode and median; analyse words with coding or discourse analysis. Then sort what the analysis shows: build the conclusion on empirical evidence and interpretations, avoid assumptions and false conclusions, never ignore results that contradict what you expected, and judge how reliable and valid your data is.

Key points

1GRaDE: General trend (including positive, negative or no correlation), Range of data, Data quotation, Exceptions.

2Mean = total ÷ number of values; mode = most common value; median = middle value in order (the midpoint of the two middle values if there's an even number).

3Coding marks areas of opinion (e.g. soc+, env-, econ-) in interview or questionnaire transcripts; discourse analysis asks how and why an article, post, advert or blog was written.

4Four types of statement: empirical evidence (directly observed), interpretation (strongly pointed to by the data), assumption (assumed true), false conclusion (no evidence it's true).

5Collecting data that tests an assumption can turn it into an interpretation.

6Confirmation bias = concluding what you already believed from only some of the evidence. For an anomaly, look first for a real geographical variable that could explain it.

7A 'to what extent' question allows a developed conclusion that weighs supporting against contradictory evidence; reliable data would give the same result on a comparably similar occasion, and valid data lets you answer the question.

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Worked example

Problem

Made-up practice data: eight people rated how clean a street is, from 1 (very dirty) to 5 (very clean). Their ratings were 4, 2, 5, 2, 1, 4, 3, 2. Find the mean, mode and median, then say what they tell you.

⚠ Watch out

Mixing up reliable and valid. Reliable means you'd get the same result if you collected it again on a comparably similar occasion. Valid means the data actually lets you answer your enquiry question. They are two separate checks, so test your data against each one.

🧠

Memory hook

Make every sentence show its ID. Seen it? Empirical evidence. Data points strongly to it? Interpretation. Just believe it? Assumption — go and test it. Nothing behind it? False conclusion — cut it.

✓

Check yourself

Write one conclusion sentence about the beach that the data supports, then one that over-claims. What exactly makes the second one go too far?

Flashcards

(14)

What does GRaDE stand for?

General trend, Range of data, Data quotation, Exceptions — the four things to describe in quantitative data before you draw a conclusion.

Positive vs negative correlation?

Positive: an increase in one variable goes with an increase in the other. Negative: an increase in one goes with a decrease in the other.

How can you tell how strong a correlation is — or whether there is one at all?

The closer the points are to the line of best fit, the stronger the correlation. If no trend line or line of best fit can be drawn, there is no correlation.

Mean, mode and median?

Mean: total of the values ÷ number of values. Mode: the most common value. Median: the middle value in numerical order — with an even number of values, the midpoint of the two middle ones.

What does 'successful analysis' of quantitative data really mean?

Correctly understanding what the numerical values mean — not necessarily being able to process and manipulate the data.

What is coding, and what is it used on?

Creating codes for areas of thought or opinion (e.g. soc+, env-, econ-) and marking where each comes up in interview or questionnaire transcripts, to find patterns of thought between respondents.

What does discourse analysis ask of an article, post, advert or blog?

How and why it was written that way — its structure and layout, language, intended audience and when it was written — not only what it says.

Which types of statement should a good conclusion rest on — and which should it avoid?

Rest on empirical evidence and interpretations. Avoid assumptions and false conclusions.

How can an assumption become an interpretation?

By collecting additional data that tests it — from primary or secondary sources.

What is confirmation bias?

Concluding what you already believe to be true by basing your ideas on some, but not all, of the evidence you collected.

What should a geographer do FIRST with an anomaly?

Look for a real-world geographical variable that could explain it — rather than ignoring it, altering it to fit, or blaming conditions, human error or equipment straight away.

When is data reliable?

When the same result would be collected on a comparably similar occasion.

When is data valid?

When it allows you to answer your enquiry question successfully.

Why does a 'to what extent' enquiry question allow a better conclusion than a yes/no one?

A yes/no question only allows a simple conclusion. 'To what extent' allows a developed conclusion that weighs supporting evidence against contradictory evidence.

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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How much is standing behind each sentence?

The result that doesn't fit

Write a developed conclusion

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