AQA GCSE Geography (8035) — Geographical applications
Planning a trip to a river or a city centre might sound like a simple day out, but for geographers, it is a carefully designed scientific investigation. AQA requires you to complete two contrasting fieldwork enquiries: one in a physical environment and one in a human environment.
Every enquiry starts with a broad Aim (what you want to achieve), which is then narrowed down into a testable Hypothesis. To be effective, a hypothesis must use directional language, stating the expected relationship using words like "increases" or "decreases".
When selecting a hypothesis, you must consider practical feasibility factors:
The SMART Criteria is the best-practice framework for designing an enquiry question. A strong hypothesis must be Specific (precise location), Measurable (quantifiable with equipment), Achievable (physically possible), Relevant (linked to geographical theory), and Time-bound (completable in one field trip).
Why do rivers get wider as they flow toward the sea, and why are city centres so heavily built up? Geographical theories provide a conceptual framework that allows us to predict these patterns and test them in reality.
In physical geography, the Bradshaw Model predicts how a river changes from its upstream source to its downstream mouth.
In human geography, urban models explain land-use patterns across a city:
You wouldn't trust a weather report from 1912 to decide if you need an umbrella today. The source and age of your data matter immensely.
Primary data is original, first-hand evidence collected by the student specifically for the hypothesis (e.g., river depth measurements or an Environmental Quality Survey (EQS)). Secondary data is second-hand information collected by a third party. Secondary sources for human geography include the Census (Office for National Statistics) or Police.uk crime stats. Physical geography sources include British Geological Survey (BGS) maps or Environment Agency flood risk data.
Here is a comparison of primary and secondary data:
| Feature | Primary Data | Secondary Data |
|---|---|---|
| Origin | Collected first-hand by the student. | Collected by a third party (e.g., ONS, Met Office). |
| Cost and Time | High cost (equipment, travel) and time-consuming. | Usually free and quick to access online. |
| Reliability | Known methodology; you can control for errors. | Unknown methodology; there may be hidden bias. |
Secondary data is crucial because it allows you to compare your primary data against historical trends or contextualise your findings within a wider geographical area.
If you wanted to find the average depth of a river, measuring every single drop of water would take lifetimes. Instead, geographers use sampling to gather a representative dataset, which reduces bias and saves time.
There are three main sampling strategies:
Choosing the right equipment is a causal mechanism for improving accuracy and validity.
Rivers can sweep you away, and city traffic can be just as dangerous. Every fieldwork enquiry requires a risk assessment to identify a hazard, calculate the risk, and apply a mitigation strategy.
Risk is calculated using a simple formula:
For example, slipping on a riverbed might have a Severity of 2 and a Likelihood of 2, giving a Risk score of 4. By applying mitigation (wearing sturdy, high-grip walking boots), the Likelihood drops to 1, halving the Risk score to 2.
Common hazards include:
When writing a hypothesis, students often forget to use directional language. Always use comparative words like 'increases', 'decreases', or 'more than' to ensure the hypothesis is testable.
Students often use vague terms like 'be careful' for risk mitigation. You must use precise, specific actions like 'check tide tables in advance' or 'wear high-visibility clothing'.
In exams, you may be asked to justify your choice of location. Always link this back to a geographical theory. For example: 'The site allowed us to test the Bradshaw Model as it had safe access to distinct upstream and downstream characteristics.'
When asked to 'justify' a data collection method, do not just describe what you did. You must explain the causal mechanism—how the specific equipment or sampling strategy improved the accuracy, reliability, or validity of your results.
Remember the '3-Mark Rule' for risk assessment questions: 1) Identify the hazard (e.g., slippery rocks), 2) State the specific risk (e.g., falling and breaking a bone), and 3) Explain the mitigation (e.g., wearing sturdy walking boots).
Aim
A broad statement explaining what the geographical enquiry is attempting to achieve.
Hypothesis
A specific, directional, and measurable statement that can be tested through data collection to be proven or disproven.
SMART Criteria
A framework ensuring an enquiry question is Specific, Measurable, Achievable, Relevant, and Time-bound.
Bradshaw Model
A geographical model that predicts how a river's characteristics, such as width and depth, change from its upstream source to its downstream mouth.
Discharge
The volume of water passing a specific point in a river per second, usually measured in cubic metres per second (cumecs).
Burgess Model
An urban land-use model suggesting that cities grow outwards from a Central Business District (CBD) in concentric rings.
Zone of Transition
An area in the Burgess model located just outside the CBD, typically containing older housing and industry with lower environmental quality.
Hoyt Model
An urban land-use model suggesting that cities develop in wedges or sectors radiating outward along major transport routes.
Bid Rent Theory
A geographical theory stating that land value and rent prices decrease as distance from the Peak Land Value Intersection (PLVI) in the CBD increases.
Primary data
Original, first-hand data collected by the student in the field, tailored exactly to the enquiry's hypothesis.
Environmental Quality Survey (EQS)
A subjective technique assigning scores to environmental indicators like litter or noise to quantify the 'feel' of a specific site.
Secondary data
Second-hand data that has been collected, interpreted, or published by someone else, such as the Census or Met Office.
Bias
A distortion in data collection where certain results are favoured over others, often reduced through objective sampling methods.
Random Sampling
A sampling strategy where every member of a population has an equal chance of being selected, often using a random number generator to reduce bias.
Systematic Sampling
A sampling strategy where data is collected at regular, fixed intervals, ensuring even coverage across a study area.
Stratified Sampling
A sampling strategy that divides a study area into sub-groups and samples proportionately from each to ensure all areas are represented.
Accuracy
The degree to which a measurement represents the true, real-world value.
Validity
The extent to which an experiment or piece of equipment actually measures what it was intended to measure.
Bipolar Scale
A quantitative scoring system (e.g., -3 to +3) used in surveys like an EQS to measure subjective opinions on environmental factors.
Reliability
The consistency of results, which can be improved by taking multiple readings and calculating a mean.
Hazard
An object, environment, or situation with the potential to cause physical harm during fieldwork.
Risk
The likelihood that a hazard will actually cause harm, multiplied by the severity of that harm.
Mitigation
A specific action taken or equipment used to reduce the severity or likelihood of a risk.
Put your knowledge into practice — try past paper questions for Geography
Aim
A broad statement explaining what the geographical enquiry is attempting to achieve.
Hypothesis
A specific, directional, and measurable statement that can be tested through data collection to be proven or disproven.
SMART Criteria
A framework ensuring an enquiry question is Specific, Measurable, Achievable, Relevant, and Time-bound.
Bradshaw Model
A geographical model that predicts how a river's characteristics, such as width and depth, change from its upstream source to its downstream mouth.
Discharge
The volume of water passing a specific point in a river per second, usually measured in cubic metres per second (cumecs).
Burgess Model
An urban land-use model suggesting that cities grow outwards from a Central Business District (CBD) in concentric rings.
Zone of Transition
An area in the Burgess model located just outside the CBD, typically containing older housing and industry with lower environmental quality.
Hoyt Model
An urban land-use model suggesting that cities develop in wedges or sectors radiating outward along major transport routes.
Bid Rent Theory
A geographical theory stating that land value and rent prices decrease as distance from the Peak Land Value Intersection (PLVI) in the CBD increases.
Primary data
Original, first-hand data collected by the student in the field, tailored exactly to the enquiry's hypothesis.
Environmental Quality Survey (EQS)
A subjective technique assigning scores to environmental indicators like litter or noise to quantify the 'feel' of a specific site.
Secondary data
Second-hand data that has been collected, interpreted, or published by someone else, such as the Census or Met Office.
Bias
A distortion in data collection where certain results are favoured over others, often reduced through objective sampling methods.
Random Sampling
A sampling strategy where every member of a population has an equal chance of being selected, often using a random number generator to reduce bias.
Systematic Sampling
A sampling strategy where data is collected at regular, fixed intervals, ensuring even coverage across a study area.
Stratified Sampling
A sampling strategy that divides a study area into sub-groups and samples proportionately from each to ensure all areas are represented.
Accuracy
The degree to which a measurement represents the true, real-world value.
Validity
The extent to which an experiment or piece of equipment actually measures what it was intended to measure.
Bipolar Scale
A quantitative scoring system (e.g., -3 to +3) used in surveys like an EQS to measure subjective opinions on environmental factors.
Reliability
The consistency of results, which can be improved by taking multiple readings and calculating a mean.
Hazard
An object, environment, or situation with the potential to cause physical harm during fieldwork.
Risk
The likelihood that a hazard will actually cause harm, multiplied by the severity of that harm.
Mitigation
A specific action taken or equipment used to reduce the severity or likelihood of a risk.
