Give a qualified answer, weigh the most important limitations and explain how each affects the conclusion.
Return to the exact question or hypothesis. State the main answer using your strongest evidence, then explain exceptions. Distinguish what the sample shows from what you can generalise to a wider population. A failure to support the prediction is not a failed investigation.
Evaluate the data and the methods used to collect and present them. Ask whether the indicators measured the intended concept, whether relevant groups and conditions were included and whether instruments or observers introduced error. Charts can also mislead through grouping, scaling or omitted denominators.
Explain consequences rather than listing flaws. "The sample was small" is incomplete. Which comparison became uncertain? Which group was absent? A justified judgement may give more weight to a biased sample than to a minor rounding issue.
Propose practical improvements linked to those consequences. Explain remaining limits and how another round of fieldwork could test the conclusion. In the 10-mark fieldwork evaluation, an analytical response applies methods to the supplied context; a memorised list of strengths and weaknesses is not enough.
Step by step
Answer and support
Use a pattern, numerical evidence and an important exception.
Weigh limitations
Explain which flaw most affects the answer and why.
Improve and qualify
Target the flaw, acknowledge the trade-off and state the conclusion's reach.
Worked example: A bounded conclusion
"Among the sampled users, shade was the most frequently reported barrier. This supports adding shade on the observed routes, but the sample excludes homebound residents and covers one morning. Before prioritising the whole neighbourhood, include non-users and repeat observations at hotter times."
Watch out for this
Mentioning limitations makes the conclusion weaker.
Relevant limits make the claim more defensible. The aim is a justified answer, not certainty beyond the evidence.
Check your understanding
Which statement best evaluates a fieldwork method?
- The survey was good because we worked hard.
- Sampling only park users omits non-users, so the result cannot represent all residents' access.
- All surveys are biased, so no conclusions are possible.