Conclusions and Evaluation of the Enquiry

From findings to an answer

A geographical enquiry starts with an aim: a question you want to answer. It may also include a hypothesis predicting what you expect to find. After collecting, presenting and analysing evidence, the conclusion brings the investigation back to that starting point.

A conclusion is more than a summary of results. It explains what those results mean for the original question. An evaluation then considers how much confidence you can place in that answer. A clear pattern can support a conclusion, but weaknesses in how the evidence was collected may limit how widely it applies.

Building an evidenced conclusion

Begin by returning to the exact aim or hypothesis. Select the findings that answer it, rather than repeating everything you recorded. Support your answer with specific evidence: relevant measurements, percentages, comparisons between named sites or patterns shown by your results.

For example, an enquiry might test whether changes in river bed-load size are linked to changes in velocity. Bed load is material transported along the river bed. A conclusion needs to consider the results for both variables, not merely describe changes in sediment size. Smaller conclusions about each dataset can lead towards an overall judgement about whether they are linked.

Consider evidence against your initial expectation as well as evidence supporting it. An anomaly may qualify the conclusion: a general pattern can exist without every site following it. Where appropriate, connect the findings to the geographical theory behind the enquiry, while keeping your explanation grounded in the evidence collected.

Finish by answering the question directly. A hypothesis may be supported, partly supported or not supported. Alternatively, the evidence may be insufficient to make a secure decision. Keep the claim within the enquiry’s scope: findings from a few sampled sites do not automatically describe an entire river or town.

Following a problem through to its consequences

Evaluation asks how effectively the enquiry answered its question. It involves reflecting on what actually happened, not producing a list of everything that could go wrong.

A useful way to develop an evaluation point is:

Problem with the method → limitation of the data → effect on the conclusion.

For example, a strong river current can cause a ruler to flex during depth measurements. The method problem is movement of the ruler; the resulting limitation is uncertainty in the recorded depths. A conclusion based on small differences in depth between sites would therefore be less secure, because some of the apparent difference might result from measurement error.

Compare this with asking only ten people to complete a questionnaire in a central business district. Even if every response is recorded accurately, the sample provides a limited range of views. It may not represent the wider population using that area. Accurate recording and a representative sample are different strengths: an enquiry needs evidence suitable for the claim it makes.

Assessing the coverage and quality of your data

Look at the sample size, sampling method, locations and timing. Did the sampling method favour particular people or sites? Were some locations inaccessible? Was a pedestrian count long enough to reflect typical activity? Data collected at one time of day provide evidence about that period, but may not justify a conclusion about the whole day.

Conditions also matter. Weather, the day or month, and unexpected events may affect the results. Equipment problems or incorrect use can reduce measurement accuracy. Questionnaire wording and environmental quality survey criteria can also influence what is recorded: consider whether they captured the information needed to answer the aim.

These limitations do not all have equal importance. A brief interruption at one site may have little effect on a strong overall pattern, whereas missing a major part of the study area may seriously restrict the conclusion. Explain the significance of each actual problem rather than assuming any weakness makes the whole enquiry worthless.

Choosing useful improvements and additional evidence

An improvement should address an identified weakness. A larger, better-distributed questionnaire sample could provide a wider range of views. Repeating pedestrian counts at different times could show whether the original pattern persists beyond the first observation period. Taking further measurements could help check whether an unusual result is repeated.

Additional data can also strengthen an explanation, rather than simply increasing the amount of existing data. In the river example, collecting velocity data alongside bed-load measurements would allow the suggested relationship to be examined. Bed-load measurements alone cannot establish that relationship.

Explain what each proposed addition would contribute and how it would affect confidence in the conclusion. Other relevant secondary evidence may provide useful comparisons, but it must help answer the original question.

Reaching a balanced judgement about reliability

The reliability of a conclusion depends on the enquiry as a whole. Relevant evidence, careful measurements and adequate coverage strengthen it. Measurement errors, unrepresentative samples and limited coverage weaken it. Errors in processing or interpreting results can also affect the final answer.

A balanced evaluation recognises both strengths and limitations. You might judge a conclusion convincing for the sampled locations and collection period, but less secure for the wider area or other times. This is more informative than simply calling the enquiry ‘reliable’ or ‘unreliable’: it explains which conclusions can be trusted, to what extent, and why.

Reaching conclusions

• Return to the original aim or hypothesis.
• Give a direct answer supported by specific results.
• Weigh supporting evidence against contradictory findings and anomalies.
• State whether the hypothesis is supported, partly supported, not supported or unresolved.
• Keep the conclusion within the locations, times and sample investigated.

Evaluating the enquiry

Use the chain: method problem → data limitation → effect on the conclusion.