The 5-Stage Enquiry Process

Stage 1: Choose an Aim or Research Question
The aim is the broad question you want to explore. It sets the direction for everything that follows. A good aim is geographically focused — it refers to a spatial pattern, a process, or a relationship. Poor aims are vague ("I want to find out about rivers") or untestable ("Is the environment nice?"). Strong aims are specific and link to geographical theory:

Example aim: "How does the urban environment change from the city centre towards the suburbs in Birmingham?"
Example aim: "How does river velocity change with distance downstream along the River Exe?"

Stage 2: Develop a Hypothesis
The hypothesis is a specific, testable prediction derived from your aim. It must be falsifiable — that is, it must be possible for your data to prove it wrong. A hypothesis based on geographical theory gives you a framework to test rather than simply describe. The standard format is:
"[Variable A] will [increase/decrease/change in a specific way] with [Variable B] because [geographical theory]."

Example: "Pedestrian counts will decrease with distance from the city centre, due to lower commercial density and footfall away from retail areas."
Example: "River velocity will increase with distance downstream because the channel becomes wider and deeper, reducing friction with the bed and banks."

The hypothesis links to a geographical model or process — the Bradshaw Model for rivers, bid-rent theory for urban land use. This shows the examiner you are not just measuring for the sake of it.

Stage 3: Design Your Data Collection
This is the planning stage — and the one where most marks are lost if students cannot justify their choices. You must decide:

• What data you need (primary or secondary, quantitative or qualitative)
• Which collection methods are appropriate for that data
• What sampling strategy you will use and why
• What equipment is needed
• What controls you will keep constant
• Your risk assessment — identifying hazards and control measures

Every decision must be justified with reference to the enquiry aim. "We used systematic sampling because we wanted to detect change along a transect" is the kind of justification that earns marks. "We used systematic sampling because it was easier" does not.

Stage 4: Collect and Present Your Data
The fieldwork itself — but collection is only half this stage. After collecting raw data, you must process and present it using the most appropriate technique. This means selecting the right graph or map for your data type, labelling axes correctly, using scales that show patterns clearly, and annotating graphs to draw attention to trends and anomalies.

Presentation choices are themselves a testable skill. The examiner may ask you to justify why you used a scatter graph rather than a bar chart, or why a choropleth map was more appropriate than a flow line for your data.

Stage 5: Analyse, Conclude, and Evaluate
The final and most heavily examined stage. Analysis identifies patterns, trends, and anomalies in your data. The conclusion answers the question: does the data support the hypothesis? Frame it as: "My results [support / do not fully support / do not support] my hypothesis because..." and cite specific data values — not just general patterns.

Evaluation is then a critical assessment of the quality of the entire investigation — the reliability of the method, the validity of the data, the representativeness of the sample, and specific, realistic improvements you would make if repeating it. This is where the highest marks live.