AQA GCSE Geography (8035) — Geographical skills
Understanding how to conduct fieldwork explains how professional geographers predict floods, plan cities, and protect coastlines. AQA requires every geography student to follow a structured sequence of enquiry when conducting a fieldwork investigation. This six-stage process guides you from asking an initial question to evaluating your final results. You must complete at least two investigations in contrasting environments (one physical, one human). Crucially, at least one investigation must examine the interaction between physical and human processes, and every investigation must include at least one method of collecting primary data firsthand.
The first stage involves selecting a location, identifying a relevant theory, and formulating a hypothesis. A geographical enquiry cannot simply be a "geography of anywhere"; it must have a place-specific context like "The River Chess". Your investigation should be underpinned by established geographical models, such as Bradshaw's Model for predicting river changes or the Burgess Model for urban land use.
For example, a physical hypothesis could be: "River velocity increases with distance from the source."
Once your hypothesis is set, you must decide how to collect data safely and without bias. A risk assessment identifies specific hazards (e.g., slippery rocks) and suggests management strategies (e.g., wearing sturdy boots with grip). Primary data is collected firsthand in the field, whereas secondary data relies on existing sources like OS maps or Census data. You must also select a sampling strategy to ensure your data is representative.
Sampling strategies ensure you collect enough valid data without having to measure everything:
Sometimes, populations are unevenly distributed. If a town has three wards with populations of 500, 300, and 200, a sample of 100 people should proportionately include 50 from Ward A, 30 from Ward B, and 20 from Ward C. This is stratified sampling: dividing a population into subsets and sampling proportionally based on known data.
After collecting data, you must choose appropriate graphical and cartographic (map-based) methods to present it visually. The method you choose depends entirely on the type of data collected. For graphical methods, use bar charts for discrete categories and line graphs for continuous data. Scatter graphs are ideal for showing correlations between two variables, while a dispersion graph shows the range and cluster of a single variable.
Cartographic methods present data spatially on a map:
Data analysis acts as the bridge between your graphs and your final conclusion. It involves identifying patterns, calculating statistics, and spotting any anomaly that does not fit the overall trend. Statistical analysis often requires calculating the interquartile range (IQR) to find the spread of the middle 50% of your data, ignoring extreme outliers.
Step 1: Order all data points from lowest to highest.
Step 2: Find the median value.
Step 3: Find the lower quartile () and upper quartile ().
Step 4: Substitute into the formula:
Finally, you must reach a conclusion by summarizing whether your original hypothesis is "supported", "partially supported", or "rejected" based entirely on your evidence.
The final stage requires critically assessing the limitations of your study and judging the reliability of your conclusions. Common limitations include small sample sizes (which lead to tentative results), timing bias (collecting data at only one time of day), or equipment error. When evaluating, you must distinguish between accuracy, reliability, and validity.
You can explicitly suggest improvements to overcome these limitations. For example, replacing a float and stopwatch with a digital flow meter improves accuracy, while repeating measurements to calculate averages improves reliability.
Students often confuse "accuracy" with "reliability." Accuracy is how close a measurement is to the true value (e.g., using a precise digital flow meter), while reliability is about consistency and whether results can be reproduced by repeating the experiment.
In 3-4 mark questions asking you to "justify the choice of your enquiry question," examiners expect you to explicitly link your question to a geographical theory (like Bradshaw's model) AND state why it was manageable with the time and equipment you had.
When asked to analyze data trends in an exam graph, use the TEA acronym: describe the overall Trend, provide specific data Evidence, and identify any Anomalies.
If asked to write your fieldwork title in the exam, ensure it includes both a specific place and a geographical concept (e.g., 'The impact of longshore drift on beach profiles at West Wittering'), otherwise it lacks the context required by examiners.
Sequence of enquiry
The six-stage structured process used to plan, carry out, and evaluate geographical fieldwork.
Fieldwork investigation
A practical study conducted outside the classroom to collect primary data and test a geographical hypothesis.
Primary data
New data collected firsthand by the researcher during fieldwork, such as pebble measurements or questionnaire results.
Secondary data
Existing data collected by someone else, such as census statistics, OS maps, or Environment Agency records.
Hypothesis
A clear, directional, and measurable statement that can be tested using fieldwork data.
Bias
A systematic error in sampling or data collection that makes the results unrepresentative of the whole population or area.
Stratified sampling
A sampling technique where a population is divided into subgroups and sampled proportionally to their actual size.
Anomaly
A data point or result that does not fit the overall pattern or trend.
Interquartile range (IQR)
A measure of statistical dispersion showing the spread of the middle 50% of a dataset, calculated by subtracting the lower quartile from the upper quartile.
Accuracy
How close a measured value is to the true, real-world value, often improved by using better equipment.
Reliability
The consistency of results, meaning that if the investigation were repeated under the same conditions, it would produce similar findings.
Validity
The extent to which the chosen fieldwork methods successfully measure what they actually intended to measure.
Enquiry question
A broad focus question that provides direction and guides the geographical fieldwork study.
Aim
A clear statement defining the overall goal or purpose of the fieldwork investigation.
Risk assessment
The process of identifying specific hazards in the field and suggesting management strategies to minimize harm.
Random sampling
A sampling strategy where every site or person has an equal chance of being selected, avoiding bias.
Systematic sampling
A sampling strategy where data is collected at regular, defined intervals (e.g., measuring river depth every 50 cm).
Dispersion graph
A type of graph used to show the range, spread, and clustering of a single variable's data points.
Choropleth maps
Thematic maps where areas are shaded or patterned in proportion to the value of a variable, such as population density.
Isoline maps
Maps containing continuous lines that connect points of equal value, such as contour lines for elevation.
Proportional symbols
A cartographic method where symbols on a map are sized according to the data value they represent.
Desire lines
Map lines showing straight connections between an origin and destination to illustrate movement, ignoring the actual route taken.
Put your knowledge into practice — try past paper questions for Geography
Sequence of enquiry
The six-stage structured process used to plan, carry out, and evaluate geographical fieldwork.
Fieldwork investigation
A practical study conducted outside the classroom to collect primary data and test a geographical hypothesis.
Primary data
New data collected firsthand by the researcher during fieldwork, such as pebble measurements or questionnaire results.
Secondary data
Existing data collected by someone else, such as census statistics, OS maps, or Environment Agency records.
Hypothesis
A clear, directional, and measurable statement that can be tested using fieldwork data.
Bias
A systematic error in sampling or data collection that makes the results unrepresentative of the whole population or area.
Stratified sampling
A sampling technique where a population is divided into subgroups and sampled proportionally to their actual size.
Anomaly
A data point or result that does not fit the overall pattern or trend.
Interquartile range (IQR)
A measure of statistical dispersion showing the spread of the middle 50% of a dataset, calculated by subtracting the lower quartile from the upper quartile.
Accuracy
How close a measured value is to the true, real-world value, often improved by using better equipment.
Reliability
The consistency of results, meaning that if the investigation were repeated under the same conditions, it would produce similar findings.
Validity
The extent to which the chosen fieldwork methods successfully measure what they actually intended to measure.
Enquiry question
A broad focus question that provides direction and guides the geographical fieldwork study.
Aim
A clear statement defining the overall goal or purpose of the fieldwork investigation.
Risk assessment
The process of identifying specific hazards in the field and suggesting management strategies to minimize harm.
Random sampling
A sampling strategy where every site or person has an equal chance of being selected, avoiding bias.
Systematic sampling
A sampling strategy where data is collected at regular, defined intervals (e.g., measuring river depth every 50 cm).
Dispersion graph
A type of graph used to show the range, spread, and clustering of a single variable's data points.
Choropleth maps
Thematic maps where areas are shaded or patterned in proportion to the value of a variable, such as population density.
Isoline maps
Maps containing continuous lines that connect points of equal value, such as contour lines for elevation.
Proportional symbols
A cartographic method where symbols on a map are sized according to the data value they represent.
Desire lines
Map lines showing straight connections between an origin and destination to illustrate movement, ignoring the actual route taken.
