AS 3: Fieldwork Skills and Techniques in Geography — The Written Report and Table of Data
Welcome to your study guide for one of the most practical and rewarding parts of your CCEA AS Geography course! In AS Unit 3 (SGG31), you step out of the textbook and into the real world. This unit tests your ability to investigate geographical processes firsthand.
Don't worry if fieldwork reports or statistical calculations feel a bit daunting right now. In this guide, we will break down exactly how to prepare your Fieldwork Summary Statement and Table of Data, how they fit into your final exam, and how to avoid the common traps that catch students out.
1. The Big Picture: How AS Unit 3 Works
Let's look at the structure of your examination so you know exactly where your report and data fit in:
• The Examination: AS Unit 3 is a 1-hour written examination worth 60 marks. It makes up 40% of your total AS Level (or 16% of the full A Level award).
• Question 1 (Fieldwork Skills): This question is based entirely on your own primary fieldwork investigation. To answer it, you will physically bring your Fieldwork Summary Statement and Table of Data into the exam hall and attach them to your answer booklet using a treasury tag.
• Question 2 (Geographical Techniques): This question tests quantitative and qualitative skills using unseen resources provided on the day.
Crucial Fact to Remember: Your submitted Summary Statement and Table of Data are not marked directly with a standalone grade. Instead, they act as the verified factual evidence against which the examiner marks your answers to Question 1. If your table and statement are well-organised, answering Question 1 becomes much easier!
2. Deconstructing the Fieldwork Summary Statement
Your Fieldwork Summary Statement (often called your written summary report) sets the scene for your entire study. Think of it like the introduction and blueprint of a science experiment. It must contain three vital elements:
A. Title and Location
Your title should state exactly what you investigated and where. A vague title like "River Study" will cost you clarity marks. Instead, use a precise geographical title such as:
• "A Study of Downstream Changes in the River Shimna", or
• "A Study of Psammosere Plant Succession at White Park Bay".
B. Fieldwork Context and Purpose
This is a concise explanation of the theoretical background of your study. For example, if you studied a river, you might mention the Bradshaw Model and explain how channel characteristics are expected to change from source to mouth.
C. Aims and Testable Hypotheses
An aim is your broad geographical goal (e.g., "To investigate changes in river channel efficiency downstream"). You must break this down into 2 to 3 specific, measurable hypotheses that can be tested with numerical data.
Good vs. Weak Hypotheses:
• Weak: "The river gets bigger downstream." (Vague: What does 'bigger' mean? How is it measured?)
• Strong: "There is a significant positive correlation between distance downstream and cross-sectional area." (Specific, measurable, and testable using statistical techniques).
Key Takeaway: Keep your hypotheses clear, focused on measurable variables, and directly tied to the numbers you actually record in the field.
3. The Table of Data: The Golden Rules
Your Table of Data is the numerical heart of your enquiry. Examiners are very strict about how this table must be formatted, so pay close attention to these rules!
Rule 1: RAW DATA ONLY!
Your table must contain only original, raw primary data collected in the field.
What must NOT be in your table: You must never include pre-calculated statistics such as averages/means, standard deviations, Spearman’s rank correlation values (\(r_s\)), or Chi-square results. All statistical calculations must be done live during the exam in your answer booklet. If you pre-calculate them on your sheet, you breach exam rubric regulations and lose the opportunity to earn calculation marks!
Rule 2: Clear Headings and Precise Units
Every single column and row must have a clear heading and state the exact units of measurement used. For example:
• Distance Downstream (\(\text{km}\) or \(\text{m}\))
• Velocity (\(\text{m/s}\) or \(\text{cm/s}\))
• Pebble Long Axis (\(\text{mm}\) or \(\text{cm}\))
• Vegetation Cover (\(\%\))
Rule 3: Clear Sample Site Identifiers
Clearly label each study location (e.g., Site 1, Site 2, Site 3... or Transect A, Transect B...) so you can easily reference specific sites in your written answers.
Quick Memory Trick: Think of R-U-S for your table:
• Raw data only (no pre-calculated stats)
• Units clearly stated on every column
• Site identifiers clearly numbered
4. The Fieldwork Enquiry Sequence
In Question 1, the examiner will ask you to reflect on different stages of your fieldwork journey. Let's walk through the full enquiry cycle so you are ready for any question.
Stage 1: Pre-Fieldwork Planning and Risk Management
Before stepping outside, geographers must plan carefully:
• Site Selection: You must be able to justify why you chose your specific sites (e.g., safe public access, representing different stages of a river profile, variation in sand dune age).
• Sampling Strategies: You must justify how you chose your sample points:
1. Systematic Sampling: Taking measurements at regular, equal intervals (e.g., measuring river depth every \(0.5\text{ m}\) across a transect, or placing a quadrat every \(5\text{ m}\) along a sand dune transect).
2. Random Sampling: Selecting points using random number tables or coordinates to eliminate human bias.
3. Stratified Sampling: Dividing the study area into distinct sub-groups or zones (e.g., embryo dunes, yellow dunes, grey dunes) and sampling proportionally within each zone.
• Risk Assessment: Identifying hazards in advance (e.g., slippery rocks, fast-flowing water, sudden tidal changes, hypothermia) and establishing practical safety mitigations (e.g., wearing non-slip wading boots, checking tide timetables, carrying first aid kits, working in groups of three).
Stage 2: Primary Data Collection and Equipment
You must be able to describe your equipment and step-by-step methods in precise detail:
• Flow Meter / Impeller: Used to measure water velocity. Held facing directly upstream at a consistent depth (e.g., \(0.6\) of the total depth from the surface) for a set time period.
• Clinometer and Ranging Poles: Used to measure slope angle / beach profile. Ranging poles are placed at slope breaks, and the clinometer is sighted at the matching height marker on the opposite pole.
• Quadrat: Used to measure percentage plant cover or species frequency across a dune system.
• Callipers or Rulers: Used to measure the long axis of sediment particles (\(\text{mm}\)).
Stage 3: Reliability vs. Validity (Don't Confuse These!)
Examiners frequently report that students mix these two terms up. Here is the simple distinction:
• Reliability (Consistency & Precision): Can you repeat the measurement and get the same result? We increase reliability by repeating measurements (e.g., timing water flow three times and averaging the results) and taking larger sample sizes to reduce anomalies.
• Validity (Accuracy & Appropriateness): Are you actually measuring what you intended to measure? We ensure validity by using the correct, calibrated equipment (e.g., using a digital flow meter rather than a floating orange on a windy day, which measures wind speed as well as water movement).
5. Data Presentation, Statistical Analysis, and Evaluation
Data Presentation
You may be asked to draw or justify a graphical technique to display your raw data:
• Scatter Graphs: Ideal for showing relationships or correlations between two continuous variables (e.g., distance downstream vs. bedload roundness).
• Bar Charts / Histograms: Great for comparing discrete categories or grouped frequencies.
• River Cross-Sections / Beach Profiles: Ideal for showing physical channel geometry and slope changes across transects.
• Bi-polar Charts: Useful for representing qualitative environmental quality survey scores.
Statistical Analysis
During the exam, you will calculate statistical techniques by hand using the figures from your Table of Data. The most common technique is Spearman’s Rank Correlation Coefficient (\(r_s\)):
\(r_s = 1 - \frac{6 \sum d^2}{n(n^2 - 1)}\)
Where:
• \(d\) = the difference between the ranks of each pair of data
• \(d^2\) = the squared difference
• \(n\) = the number of pairs of data / sample size
Once you calculate your \(r_s\) value (which always falls between \(-1.0\) and \(+1.0\)), you compare it against a critical values significance table to determine if your correlation is statistically significant at the \(0.05\) (\(95\%\)) or \(0.01\) (\(99\%\)) confidence level.
Geographical Interpretation and Evaluation
After calculating your statistics, you must evaluate what the numbers actually mean:
• Do your findings support or reject your original hypothesis?
• How do your findings connect back to academic geographical models (e.g., the Bradshaw Model)?
• What were the limitations of your investigation (e.g., seasonal weather conditions, restricted site access, operator error), and how could you improve the study if you repeated it?
6. Top Examiner Pitfalls to Avoid
Make sure you don't fall into these common exam traps:
1. Writing "Generic" Textbook Answers: Never give vague answers like "We measured velocity with a flow meter." Always use specific details from your own study: "At Site 3 on the River Shimna, we used an OTT digital flow meter held at \(60\%\) depth for \(30\text{ seconds}\), recording a velocity of \(0.42\text{ m/s}\)."
2. Including Pre-Calculated Stats: Leaving calculated averages or \(r_s\) values in your table breaks the rules. Keep your table 100% raw data.
3. Vague Hypotheses: Ensure your hypotheses mention measurable variables that are present in your table columns.
4. Forgetting the Treasury Tag: Remember to securely tag your Fieldwork Summary Statement and Table of Data to your answer booklet before handing it in!
Quick Summary Review
• AS Unit 3 (SGG31) contributes 40% to your AS qualification.
• Summary Statement: Contains Title/Location, Fieldwork Context, and 2–3 Testable Hypotheses.
• Table of Data: Contains strictly raw data with clear column headings, units, and site numbers — no pre-calculated statistics.
• Question 1 Strategy: Always quote actual numbers, specific site names, and exact equipment from your own investigation.
• Reliability vs. Validity: Reliability = repeats and consistency; Validity = right tools and true accuracy.