Fieldwork skills: the geographical enquiry process

OCR J383 Paper 3 devotes significant marks to fieldwork methodology questions. You must understand the full enquiry process — from formulating a question to evaluating your results — and be able to suggest appropriate methods for both physical and human geography investigations.

The fieldwork enquiry cycle

The enquiry follows a structured sequence:

1. Formulate a question or hypothesis
2. Plan data collection (methods, sampling, risk assessment)
3. Collect data (primary fieldwork + secondary research)
4. Process and present data (graphs, maps, statistics)
5. Analyse and interpret data (patterns, trends, anomalies)
6. Evaluate (limitations, reliability, improvements)
7. Reach a conclusion (linked back to the original question)

OCR Paper 3 (Section B) asks you to apply this cycle to an unfamiliar scenario or reflect on your own compulsory fieldwork enquiries.

Step 1: Formulating a question or hypothesis

A good enquiry question:

• Is geographically focused (links to a spec topic).
• Is answerable with data you can realistically collect.
• Is not too broad ("How do rivers work?") or too narrow ("How does one pebble change?").

Hypothesis: a testable statement predicting a relationship.

• Example (rivers): "Discharge increases downstream along the River Exe."
• Example (urban): "Environmental quality decreases from the CBD to the inner city in Manchester."

Null hypothesis: the prediction that there is NO relationship — allows statistical testing (Spearman's rank).

Step 2: Data collection methods

Primary data (collected yourself in the field)

Physical geography methods (rivers):

Method	What it measures	How
River velocity	Speed of flow (m/s)	Float a dog biscuit 10 m downstream; time with stopwatch; repeat 3×
River width	Channel width (m)	Tape measure bank to bank
River depth	Channel depth (m)	Measuring stick at regular intervals across channel
Discharge	Volume of water (m3/s)	Width × average depth × velocity
Pebble sampling	Sediment size (mm)	Randomly pick 20 pebbles; measure long axis with Cailleux calliper
Channel cross-section	Shape of channel	Tape measure + measuring stick at regular intervals

Human geography methods (urban/rural):

Method	What it measures	How
Environmental Quality Survey (EQS)	Perceived quality of environment	Bipolar scoring (e.g. −5 to +5) on criteria (litter, noise, greenery)
Land use survey	Type of buildings/businesses	Annotated map; tally of land use categories
Pedestrian count	Footfall	Count people passing a fixed point in 5-minute intervals
Questionnaire/interview	Opinions, perceptions	Structured or semi-structured; sample of passers-by
Index of Multiple Deprivation	Deprivation level	Secondary data from government census
Traffic count	Vehicle type and volume	Count at fixed point; record vehicle category

Secondary data

• Census data (ONS), IMD rankings, Environment Agency river gauging data, OS maps, aerial photography, news reports, academic papers.
• Advantage: free, large dataset, long time series.
• Limitation: may be outdated; collected for different purposes; cannot always verify methodology.

Step 3: Sampling strategies

Why sample? You cannot measure everything — sampling gives a representative subset.

Sampling method	How	When to use	Advantage	Limitation
Random	Random number tables/generator assigns sample points	When population is uniform; to eliminate bias	No bias	May cluster accidentally
Systematic	Every nth item or at regular intervals (every 10 m)	When data distributed evenly	Easy; ensures coverage	May miss variation between intervals
Stratified	Population divided into groups; random sample from each group	When groups within a population are important	Representative of all groups	Complex; need to know group sizes first
Opportunistic	Sample whoever/whatever is convenient	When access is limited	Practical	High bias; not representative

River study: systematic sampling — measure river at every 100 m downstream. Urban questionnaire: stratified sampling — ensure representation by age and gender.

Step 4: Data presentation techniques

Technique	When to use
Scatter graph	Show relationship between two variables (e.g. discharge vs distance from source)
Line graph	Show change over time or distance
Bar chart / histogram	Compare categories; show frequency distribution
Proportional symbol map	Show data that varies spatially by quantity
Choropleth map	Show data by area with shading (e.g. deprivation by ward)
Kite diagram	Show species distribution across a transect
Cross-section / long profile	Show river or coastal profile
Spearman's rank (Rs)	Test strength of correlation between two ranked variables

Spearman's rank: value from −1 (perfect negative correlation) to +1 (perfect positive correlation). Rs > 0.7 = strong positive; Rs < −0.7 = strong negative; Rs 0 = no correlation.

Step 5: Analysis and evaluation

Analysis

• Describe the pattern: overall trend, and any anomalies (outliers).
• Explain the pattern: use geographical knowledge to explain why the data shows what it shows.
• Reference specific data points: "At site 3, discharge was 2.4 m3/s, compared to 0.3 m3/s at site 1 — a 700% increase."

Evaluation framework

• Reliability: did different people get the same result? (Inter-observer reliability)
• Validity: does the method actually measure what it claims to measure?
• Sources of error: random error (natural variation) vs systematic error (flawed method).
• Improvements: how could the method be better? (More sites, longer counts, different weather conditions)
• Limitations of secondary data: may be out of date; missing local detail.

Common OCR exam mistakes

1. Describing what you did without explaining why you chose that method — always justify choices.
2. Confusing random and systematic sampling — "I walked around and picked pebbles" = opportunistic (often biased); "I used a random number table" = random.
3. Not evaluating in the evaluation section — saying "the results were accurate" without justification scores nothing; identify specific limitations.
4. Forgetting to link conclusion back to the original hypothesis.