Introduction to Fieldwork in AS Geography
Welcome to AS 3: Fieldwork Skills and Techniques in Geography! Fieldwork is where geography truly comes alive. Instead of just reading about rivers, coasts, or urban spaces in a textbook, you get out into the real world to test geographical theories for yourself.
In the CCEA specification, Unit AS 3 is assessed through a 1-hour written examination. It is worth 20% of your total AS Level (and 10% of your full A Level). Unlike other exam boards where you might submit a long coursework project (NEA), CCEA tests your fieldwork knowledge through an external written exam where you answer questions based on your own investigation.
Don't worry if this sounds intimidating at first! This guide will break down the entire fieldwork process step-by-step so you can walk into your exam feeling completely confident.
The Fieldwork Summary Report: Rules and Conventions
Before you sit your AS 3 exam, you will prepare a short summary report of your fieldwork to bring into the exam room. CCEA has very strict rules for this report, and following them is essential:
• Strict 100-Word Limit: The written text of your summary report must be no more than 100 words. It must include the title of your study, your research question or hypothesis, and the precise location of your study site.
• Raw Primary Data Table Only: Your report must include a table of your primary data. A critical rule to remember: this table must contain raw data only! It must NOT include any calculations (such as mean values, totals, or statistical results like Spearman’s Rank). Processing your data happens during the exam, not on your summary sheet.
• Maps and Illustrations: CCEA has confirmed that maps, diagrams, or photographs are not necessary on your summary report.
Key Takeaway: Keep your summary report under 100 words, clearly state your title, hypothesis, and location, and make sure your data table contains only pure, raw data with zero calculations.
Stage 1: Planning Your Investigation
Every successful geographical investigation begins with careful planning. You cannot just turn up at a river or a town center and start measuring things randomly!
1. Formulating Aims and Hypotheses
An aim states the general purpose of your study (e.g., "To investigate changes in river channel characteristics downstream"). A hypothesis is a specific, testable prediction based on geographical theory (e.g., "Bedload particle size decreases with distance from the source").
2. Selecting and Justifying Your Location
In the exam, you must be able to justify why your chosen site was suitable. Good justifications include:
• Safe accessibility (e.g., public footpaths, safe river access points).
• Clear geographical features that allow you to test your hypothesis (e.g., an unobstructed stretch of river spanning upper to lower stages).
• Proximity and manageable scale within the time available.
3. Risk Assessment: Hazards and Mitigation
Safety is paramount. A risk assessment identifies potential hazards and explains how you will minimize the risk of harm (mitigation):
• Hazard: Slippery river beds or uneven terrain causing slips, trips, and falls. Mitigation: Wear sturdy footwear with good grip (e.g., waders or walking boots) and walk carefully.
• Hazard: Deep or fast-flowing water causing drowning risk. Mitigation: Measure water depth before entering, never enter water above knee height, and use ranging poles for stability.
• Hazard: Cold or inclement weather leading to hypothermia. Mitigation: Check weather forecasts in advance, wear warm and waterproof layers, and carry emergency blankets.
Key Takeaway: Always provide site-specific risks and actionable solutions rather than generic statements like "be careful around water."
Stage 2 & 3: Data Collection and Sampling Techniques
Primary vs. Secondary Data
• Primary Data: Any data that you collect yourself firsthand in the field (e.g., pebble size measured with calipers, river velocity measured with an impeller, or pedestrian counts).
• Secondary Data: Information collected by someone else that you use to support your study (e.g., Census data, Environment Agency flood risk maps, or historical weather records).
Sampling Techniques
Sampling allows you to collect a representative slice of data without having to measure every single object or person in an area.
1. Random Sampling
Every item in the study area has an equal chance of being selected. For example, using a random number generator to pick grid coordinates across a field site.
• Advantage: Removes human researcher bias.
• Disadvantage: Can lead to uneven coverage or miss key features by chance.
2. Systematic Sampling
Data is collected at regular, predetermined intervals. For example, taking a pebble measurement every \(2\text{ m}\) across a river transect, or recording infiltration rates every \(10\text{ m}\) along a slope.
• Advantage: Simple to organize and ensures even coverage across a distance.
• Disadvantage: Can accidentally align with an underlying pattern in the landscape, creating bias.
3. Stratified Sampling
The population or landscape is divided into distinct subgroups (strata) first, and samples are taken from each subgroup in proportion to its size. For example, selecting \(60\%\) of your river samples from a riffle section and \(40\%\) from a pool section because that matches the river's layout.
• Advantage: Guarantees all sub-environments or groups are fairly represented.
• Disadvantage: Requires prior knowledge of the study area to divide it into strata accurately.
Memory Trick: Remember R-S-S: Random (pure chance), Systematic (regular spacing), Stratified (split into groups).
Stage 4: Data Presentation Techniques
Once you have collected your data, you must present it clearly. In the exam, you will need to justify why a specific presentation technique was appropriate for your data type:
• Scatter Graphs: Ideal for showing the relationship or correlation between two continuous variables (e.g., distance downstream on the \(x\)-axis vs. pebble roundness on the \(y\)-axis).
• Proportional Circles: Ideal for displaying quantitative data geographically across a map (e.g., the size of the circle represents the volume of traffic or pedestrian flow at different survey points).
• Isoline Maps: Ideal for showing continuous spatial data by connecting points of equal value with lines (e.g., contour lines for elevation, isobars for atmospheric pressure, or travel time isolines).
Key Takeaway: Never just name a graph; explain why it fits your data (e.g., "A scatter graph was chosen because both variables are continuous and it allows a line of best fit to be drawn to identify correlations").
Stage 5: Data Analysis, Interpretation, and Statistical Skills
The Difference Between "Describe" and "Explain"
This is one of the most important distinctions in AS Geography:
• Describe: State what the pattern or trend is (e.g., "As distance from the river source increases, median sediment size decreases from \(12\text{ cm}\) to \(3\text{ cm}\)").
• Explain: Use geographical theory to explain why that pattern occurs (e.g., "Sediment decreases in size due to attrition, where bedload particles continuously collide with one another, chipping off sharp edges and breaking into smaller pieces").
Statistical Skills for AS Fieldwork
You must be able to calculate and interpret key statistical measures:
1. Measures of Central Tendency
• Mean: The mathematical average (add all values and divide by the total number of values).
• Median: The middle value when all numbers are arranged in ascending order. (Less affected by extreme outliers than the mean).
• Mode: The most frequently occurring value in a data set.
2. Measures of Dispersion
• Range: The difference between the highest and lowest values: \(\text{Range} = \text{Maximum} - \text{Minimum}\).
• Interquartile Range (IQR): The spread of the middle \(50\%\) of data values: \(\text{IQR} = Q_3 - Q_1\). It ignores extreme values, making it a reliable measure of spread.
3. Correlation (Spearman’s Rank Correlation Coefficient)
Spearman’s Rank (\(r_s\)) measures the strength and direction of a relationship between two ranked variables:
• A result close to \(+1\) indicates a strong positive correlation.
• A result close to \(-1\) indicates a strong negative correlation.
• A result close to \(0\) indicates no correlation.
Stage 6: Conclusions and Evaluation
The final stage of any fieldwork investigation is looking back critically at what you found and how you found it.
1. Drawing Geographical Conclusions
Summarize your findings directly in relation to your original aim and hypothesis. Did your results support or reject your hypothesis? Reference your data values to prove your point.
2. Critical Evaluation and Limitations
No fieldwork is perfect. A top-level evaluation identifies specific sources of error:
• Equipment Error: Inaccuracies from tools (e.g., a flowmeter propeller getting clogged by river weeds, or calipers slipping on irregular rocks).
• Sampling Bias: Sample sizes that were too small, or sampling only easily accessible locations (e.g., only sampling river banks near footbridges).
• Temporal (Time/Weather) Limitations: Measuring river discharge on a single dry afternoon, which may not represent typical seasonal river conditions.
Summary of Common Pitfalls to Avoid
• Pitfall 1: Including Calculated Data in Your Report Table. Remember that CCEA rules require raw data only. Do not include calculated averages or Spearman's Rank values.
• Pitfall 2: The "Geography of Anywhere." Always anchor your answers to your specific fieldwork location (e.g., naming your specific river, tributary, or coastal stretch).
• Pitfall 3: Generic Risk Assessments. Avoid vague statements like "take care." Name the specific hazard, its consequence, and the precise mitigation strategy.
• Pitfall 4: Forgetting to Justify Methods. When asked about sampling or data presentation, always explain why that method was the best choice for your study.