A Level H2 Geography Fieldwork Quiz

A-Level Geography H2 Quiz - Fieldwork (Answer Key)

Total Marks: 50

Section A: Research Design & Methodology

1. Sampling Strategy for River Sediment

• Strategy: Systematic Sampling. [1]
• Justification: It ensures even coverage of the entire 5km stretch (e.g., every 500m), allowing for the identification of downstream trends/patterns which random sampling might miss. [2]
  (Accept Stratified if justified by distinct reaches, but Systematic is standard for longitudinal river profiles.)

2. Operationalisation

• Definition: The process of defining abstract concepts into measurable variables. [1]
• Example: 'Urban environmental quality' could be operationalised by creating an index based on measurable indicators such as noise levels (decibels), litter count (number of items per m²), and building condition (scored 1-5). [2]

3. Systematic vs. Random Sampling (Coastal Transect)

• Advantage of Systematic: Easier to implement in the field; ensures regular intervals which helps in identifying spatial patterns/trends along the transect. [2]
• Disadvantage of Systematic: May miss specific features if the interval coincides with a periodic pattern (bias); less representative of the whole population if the starting point is biased compared to true random. [2]
  (Must compare both. 1 mark for valid advantage, 1 for valid disadvantage.)

4. Controlled Variables (Infiltration Rates)

• Variable 1: Soil moisture content/Antecedent rainfall. [1]
  • Reason: Wet soil infiltrates slower than dry soil; varying moisture would invalidate the comparison between land uses. [1]
• Variable 2: Volume of water poured/Duration of test. [1]
  • Reason: Different volumes or times would yield different infiltration rates regardless of land use, making the data incomparable. [1]

5. Primary vs. Secondary Data (Traffic)

• Primary Data: Data collected firsthand by the student. Example: Counting vehicles at a junction for 15 minutes. [1]
• Secondary Data: Data collected by someone else. Example: Traffic flow statistics from the Land Transport Authority (LTA) website. [1]

Section B: Data Collection & Risk Assessment

6. Beach Profile Method

• Place two ranging poles a fixed distance apart (e.g., 5m or 10m) along the transect line. [1]
• One student holds the clinometer at eye level (or a fixed height) on the lower pole and sights the mark on the higher pole. [1]
• Record the angle of slope (degrees) and the horizontal distance. [1]
• Repeat this process up the beach from the water line to the backshore to construct the profile. [1]

7. Safety Hazards (River Water Quality)

• Hazard 1: Slipping on muddy/slippery banks or submerged rocks. [1]
  • Mitigation: Wear appropriate footwear (wellington boots/studded shoes); work in pairs/buddy system. [1]
• Hazard 2: Waterborne diseases/bacteria (e.g., Leptospirosis) from contact with water. [1]
  • Mitigation: Wear gloves when handling water/samples; wash hands thoroughly after fieldwork; cover any open cuts. [1]

8. Importance of Pilot Studies

• Benefit 1: Identifies flaws in the methodology or equipment (e.g., stopwatch batteries dying, clinometer difficult to read). [2]
• Benefit 2: Helps refine data collection sheets and estimate the time required for each sample, ensuring the main study is feasible within the time limit. [2]

9. Reliability of Likert Scales

• Evaluation: Low reliability due to subjectivity. [1]
• Reason: Different students may interpret "aesthetically pleasing" differently (inter-observer bias). One student’s '3' might be another’s '4'. [2]
  (Accept discussion of consistency if repeated by same person, but focus on subjectivity is key.)

10. Multiple Subsamples (Sediment)

• To account for local variability/anomalies (e.g., one unusually large boulder). [1]
• Taking multiple samples allows for the calculation of a mean, which provides a more representative and reliable value for that specific site. [1]

Section C: Data Presentation & Analysis

11. Graph for Pedestrian Counts (Spatial Variation)

• Type: Line Graph or Bar Chart (if discrete sites) plotted against distance/location. [1]
• Justification: A line graph effectively shows continuous trends and gradients along the transect/spatial sequence, making it easy to identify peaks and troughs in pedestrian flow. [2]
  (Bar chart is acceptable if sites are distinct categories, but line is better for transects.)

12. Mean vs. Median (House Prices)

• Distribution: The data is positively skewed (has outliers/extremely high values). [1]
• Explanation: The mean is pulled up by extreme high-value properties, whereas the median is resistant to outliers and represents the 'typical' house price better. [2]

13. Advantage of GIS

• Advantage: Ability to layer multiple datasets (e.g., overlaying flood risk maps with land use data) for complex spatial analysis. [1]
• OR: Easy to update and manipulate data digitally; allows for 3D visualization. [1]

14. Correlation vs. Causation

• Answer: No. [1]
• Explanation: Correlation indicates a relationship, but other variables (confounding factors) could cause both changes. Causation requires theoretical proof and control of other variables. [1]

Section D: Evaluation & Conclusion

15. Validity

• Definition: The extent to which the data/method measures what it claims to measure (i.e., does the test actually answer the research question?). [1]

16. Critique of "Proven"

• Critique: In science/geography, hypotheses are supported or rejected, never "proven" absolutely, as new evidence could emerge. [1]
• Alternative Term: "Supported," "Substantiated," or "Validated." [1]

17. Human Error vs. Systematic Error

• Difference: Human error is random/inconsistent (e.g., misreading once); systematic error is consistent and directional (e.g., tape measure always reads 1cm short). [1]
• Impact on Accuracy: Systematic error affects accuracy more significantly because it shifts all results in one direction, making the entire dataset inaccurate, whereas random human errors may cancel out. [2]

18. Improving Reliability (Urban Heat Island)

• Suggestion 1: Repeat measurements at different times/days to account for temporal variations (weather). [1]
• Suggestion 2: Use calibrated digital thermometers instead of analogue ones to reduce reading error. [1]
  (Other valid answers: Increase sample size, use multiple observers and average results.)

19. Linking to Theory

• Reason: To demonstrate that the fieldwork findings are not just isolated observations but can be explained by, or challenge, existing geographical models/concepts (e.g., Bid Rent Theory, Bradshaw Model). [1]

20. Limitations of Bi-polar Evaluation

• Limitation 1: It simplifies complex environments into single scores, losing nuance. [1]
• Limitation 2: It is highly subjective; different respondents may have different baseline standards for what constitutes "good" or "bad." [1]