Fieldwork: physical and human enquiries
AQA requires two contrasting fieldwork enquiries — one in a physical environment, one in a human environment. Paper 3, Section B (24 marks) tests your fieldwork on both your own enquiries (12 marks) and an unseen enquiry (12 marks).
The six stages of an enquiry
- Question or hypothesis — what are you trying to find out?
- Risk assessment and methods — how will you collect data, what dangers and how to mitigate?
- Data presentation — graphs, maps, charts.
- Analysis — what patterns/correlations does the data show?
- Conclusion — does the evidence support the hypothesis? Why?
- Evaluation — how reliable was your enquiry? What would you improve?
Choosing the question
A good enquiry question is:
- Specific — "Is the upper Lyn shallower than the lower Lyn?" not "What about the river?"
- Measurable — uses numerical data.
- Linked to a geographical concept — Bradshaw Model (rivers); CBD/zonal models (urban).
A hypothesis is a testable prediction. e.g. "The river will get deeper, wider and faster downstream."
Sampling
- Random — every site has equal chance. Reduces bias but may miss key sites.
- Systematic — every nth site (e.g. every 100 m along a river).
- Stratified — sample from each stratum (e.g. high street vs side road).
Ten sites is a good GCSE benchmark for both kinds of enquiry.
Physical fieldwork example — river characteristics
Question: Does the River Lyn fit the Bradshaw Model?
- Methods: At each site (1) measure width with tape, (2) depth at 5 points across with metre rule, (3) velocity with a flowmeter or float over 10 m, (4) bed load size with a ruler / Power's Roundness Index.
- Data presentation: line graph of velocity vs distance downstream; cross-section diagrams; scatter graph of width vs depth.
- Analysis: width and depth increase downstream as predicted; velocity also rises (less friction in larger channel).
- Conclusion: data supports Bradshaw Model.
- Evaluation: only 8 sites (low n); single day of measurement; flowmeter calibration uncertain.
Human fieldwork example — quality of life across an urban area
Question: Does environmental quality improve from the inner city to the suburbs?
- Methods: Environmental Quality Index (EQI) at 8 sites — rate 5 features (litter, traffic noise, building condition, green space, air quality) on a 1–5 scale; pedestrian counts; questionnaires (50 respondents).
- Data presentation: choropleth map shading EQI scores; bar chart of pedestrian counts; pie chart of questionnaire responses.
- Analysis: EQI scores correlate positively with distance from CBD (r = 0.72).
- Conclusion: yes — supports Burgess concentric zone model.
- Evaluation: small questionnaire sample; EQI is subjective; weather affected pedestrian counts.
Risk assessment
Examiners increasingly ask about safety. State the risk (slipping in river), the likelihood (medium), the mitigation (waders, partner system, supervisor on bank).
⚠Common mistakes— Common errors
- Generic "improve sample size" — say how many, not "more".
- Confusing precision and accuracy — define them.
- Ignoring sources of error (instruments, weather, observer bias).
- Drawing conclusions beyond the data.
Examiner tips
- For 6/9-mark fieldwork questions, always name your fieldwork (River Lyn, Bourton-on-the-Water EQI). Generic answers earn limited marks.
- For evaluations, give specific improvements ("collect on three days to even out weather", not just "more data").
- Practise interpreting unseen graphs — they will be unfamiliar but the techniques (correlation direction, anomalies, range) transfer.
AI-generated · claude-opus-4-7 · v3-deep-geography