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Evaluate Your Enquiry

Almost every candidate writes that they would have liked more time. It names nothing, explains nothing and fixes nothing, and it is worth almost no marks. A useful evaluation says which specific thing was wrong, what that did to the result, and what would put it right. How to conclude without overreaching, what to do with the reading that does not fit, and the difference between a measurement you could repeat and one that actually measures what you claim.

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Where the marks actually are

Section B of Paper 3 is worth 39 marks, and the questions that carry the most of them are rarely about what you did. They are about how far you can trust it. The final two strands of the enquiry process, reaching a conclusion and evaluating it, are where a competent piece of fieldwork turns into a good answer or fails to. Almost every candidate writes some version of the same sentence: we would have liked more time, or we should have collected more data. Read it as an examiner. It does not say what was wrong, it does not say what difference it made, and it does not say what would have been better. It is a complaint rather than an evaluation, and it earns close to nothing. What earns marks is specificity with consequences. Not that the sample was small, but that measuring at three sites along four kilometres cannot show a trend that is claimed for the whole river, and that six sites at closer spacing would test it properly. Not that the weather was poor, but that the pedestrian count was taken in heavy rain, which suppressed the numbers at the two open sites and not at the covered one, so the comparison between them is not sound. Each of those names a thing, states its effect and proposes a fix. The same standard applies to your conclusion. A conclusion has to answer the question you actually asked, use your own figures as evidence, and stop where the data stops. This module covers both strands: concluding honestly, and evaluating in a way that is worth reading. The earlier strands belong to the sibling modules.

Five terms for the end of an enquiry

The middle three are distinctions that questions test directly, and students routinely treat all three as the same idea.

Order the end of the write-up

These six steps take an enquiry from analysed data to a finished evaluation. Put them in order.

  • Return to the question or hypothesis you set out with
  • State whether the data supports it, supports it partly, or does not
  • Quote your own figures as the evidence for that statement
  • Account for any readings that did not fit the pattern
  • Identify specific weaknesses in the method and the data, and what each did to the result
  • Say what further data or change of method would make the conclusion more trustworthy

Why is "more time" worth nothing?

A candidate evaluates their enquiry by writing that with more time they could have collected more data. Which answer explains why this earns almost no credit?

  • It identifies no particular weakness, so the examiner cannot tell whether the candidate has noticed anything about their own method; it states no consequence, so nothing follows from it about whether the conclusion can be trusted; and it proposes nothing testable, since more of everything is not a plan. The same sentence could be attached to any enquiry ever carried out, which is exactly the sign that it is not an evaluation of this one. What is wanted is a named weakness, its effect on the result, and a specific change that would address it.
  • It is too negative about the work, and evaluations should emphasise strengths.
  • It is untrue, because groups are always given enough time.
  • It is too short, and evaluations need to be several paragraphs long.

Where to look, and what to do about it

Weaknesses live in the method, in the data, or in both, and each has a matching improvement. Read the rows across: the third column is what turns a criticism into an evaluation.

Match each weakness to its consequence

  • Measurements taken at only three points along a four kilometre stretch
  • Sites chosen because a footpath reached the water there
  • A street survey carried out during heavy rain
  • An environmental quality score given out of five by one member of the group
  • A trend claimed for the whole length rests on very few points, so it may be an artefact of exactly where the readings happened to fall
  • The stretch sampled is the accessible stretch rather than a representative one, and accessible places often differ systematically from the rest
  • Numbers were suppressed unevenly, since sheltered locations lost fewer people than exposed ones, so comparison between them is distorted
  • The figure is repeatable if the same person applies the same scale, and still rests on a judgement that another person might make differently

Name it, trace it, mend it

Every sentence in a good evaluation does three jobs. Name the specific weakness, in your enquiry rather than in fieldwork generally. Trace what it did to your result, because a weakness with no consequence is not worth raising. Mend it, by proposing a change precise enough that someone could actually carry it out. Miss any one of the three and the sentence stops being evaluation. A quick test for whether you have managed it: could the sentence be lifted into somebody else's write-up without alteration? If it could, it is describing fieldwork in general rather than assessing yours, and that is the fault behind almost every low-scoring evaluation. Two traps worth avoiding. The first is deleting the reading that spoils the pattern. That reading is evidence, and the reason behind it is often the most interesting thing you found; a tributary, a drain, a closed road. Explain it and say whether you kept it in the analysis. The second is confusing two different questions about trust. Asking whether you would get the same numbers again is one question; asking whether those numbers capture the thing you say they capture is another. A survey can be entirely repeatable and still be measuring something other than what its title claims. Finally, be willing to conclude that your enquiry could not settle its own question. That is an honest finding and it is marked as one. A candidate who reports a weak or mixed result and explains clearly why the method could not resolve it will score better than one who states a confident conclusion the data does not carry.

Complete the evaluation facts

Section B of Paper 3 carries _____ marks, and the questions worth most of them ask how far your work can be trusted rather than what you did. A reading that breaks the pattern is called an _____, and it should be accounted for rather than quietly removed, because whatever produced it is frequently the sharpest piece of geography the work turned up. Two separate questions decide how much weight a result carries: whether repeating the method would produce the same figures, which is _____, and whether those figures capture what you claim they capture, which is validity. A useful criticism of your own work always states the weakness, what it did to the _____, and a change specific enough to be carried out. Reporting that your data failed to settle the question is a _____ outcome and is marked as one.

39 anomaly reliability result legitimate 37 error validity method weak

Spot the three sound statements

Select the THREE statements that are true about concluding and evaluating.

  • If a sentence in your evaluation could be pasted unchanged into somebody else's write-up, it is not assessing your enquiry, which is why generic complaints about time and resources score so poorly.
  • A reading that breaks the pattern should be explained rather than removed, since the cause of it is frequently the most revealing geography the enquiry produced.
  • Whether a method would give the same answer twice and whether it measures what it claims to are separate questions, so a method can be perfectly consistent and still be pointed at the wrong quantity.
  • An evaluation should concentrate on the strengths of the enquiry so that the examiner sees it was carried out well.
  • A conclusion should always state a clear result, even where the data does not really support one.
  • The strongest improvement to suggest is always collecting more data.

A marked evaluation

Evaluate the reliability of the conclusions you reached in one of your fieldwork enquiries. [9 marks] The worked answer below uses an invented enquiry as a model of the shape. Yours must describe your own. "My enquiry asked whether the width and depth of the River Wye increase with distance downstream, and my data supported it: mean width rose from 2.4 m at site one to 7.1 m at site three, and mean depth from 0.18 m to 0.46 m. The conclusion is reasonably trustworthy for the stretch I measured and considerably less so beyond it. The main limitation is the number of sites. Three points across four kilometres is a very thin basis for a trend, and because each site contributes a third of the evidence, a single unrepresentative site would distort the whole result; six sites at closer spacing would test the pattern properly. A second limitation is where those sites were: all three were places a footpath reached the water, and accessible banks tend to be gentler and less overgrown than the rest, so my sample is probably biased towards wider, shallower sections. Choosing sites by measured distance and accepting a longer walk would reduce this. Third, depth was measured with a metre rule at five points across the channel and averaged, which improves reliability over a single reading, but different members of the group judged the bed level differently where it was soft, so the depth figures are less consistent than the width figures. One reading was anomalous: site two gave a width of 6.8 m, close to site three, which I think is explained by a tributary entering just upstream, and I have kept it in because it is a real feature of the river rather than a mistake. Repeating the work after a period of heavy rain would show whether the pattern holds at higher flow, which my single dry-day visit cannot establish." What earned the marks: the conclusion quoted with its own figures and its scope limited explicitly to the stretch measured; three separate limitations, each naming the weakness, tracing its effect and proposing a specific remedy; an anomaly explained and retained with a reason; and a final improvement that would test the explanation rather than simply gather more of the same.

Find the two real evaluations

Five sentences from the evaluation section of a write-up. Three of them could be pasted into anybody's enquiry unchanged. Tap the TWO that genuinely assess this one.

  • All three sites were places a footpath reached the water, so the sample is probably biased towards gentler, more accessible banks than the stretch as a whole.
  • With more time we could have collected more data and improved our results.
  • Where the bed was soft, different members of the group judged its level differently, so the depth readings are less consistent than the width readings.
  • The weather was not ideal on the day of the fieldwork.
  • We tried to be as accurate as possible when taking all of our measurements.

Build an evaluation sentence

Assemble a criticism that does all three jobs at once.

Four decisions at the write-up stage

The data is collected and analysed. Each choice now decides how much the work is worth.

  • One of your readings is well outside the pattern of the others. Somebody suggests leaving it out so the graph looks cleaner.
  • Your data does not clearly support or contradict your hypothesis. The result is simply mixed.
  • You are asked what further data would strengthen the enquiry. Your first instinct is to say more of the same measurements.
  • You have written four sentences of evaluation and want to know whether they will score.

Evaluate your own enquiry

Using ONE of your own fieldwork enquiries, state your conclusion and evaluate how far it can be trusted. [9 marks]

  • Your own figures quoted as evidence
  • A few sites cannot describe a whole river, street or coastline
  • Each limitation: the weakness, its effect on your result, and a change precise enough to carry out
  • The anomaly explained, and whether you kept it in the analysis
  • New data that tests your explanation, rather than repeating measurements