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A Level H2 Geography Fieldwork Quiz

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Questions

A-Level Geography H2 Quiz - Fieldwork

Name: __________________________
Class: __________________________
Date: ___________________________
Score: _______ / 50

Duration: 60 Minutes
Total Marks: 50
Topic: Geographical Investigation (Fieldwork)

Instructions:

Answer all questions.
Marks are indicated in brackets [ ] at the end of each question or part question.
Where data or resources are referenced, assume standard A-Level Geography H2 fieldwork contexts (e.g., river studies, urban environmental quality, coastal processes).
Use precise geographical terminology and refer to specific methodological concepts (e.g., validity, reliability, bias, sampling).

Section A: Research Design & Methodology (15 Marks)

1. A student is investigating the change in sediment size along a 5km stretch of a river.
State the most appropriate sampling strategy to select sites along the river course and justify your choice. [3]

2. Define the term 'operationalisation' in the context of geographical fieldwork and provide one example of how the concept of 'urban environmental quality' might be operationalised. [3]

3. Explain one advantage and one disadvantage of using systematic sampling compared to random sampling when conducting a transect survey in a coastal environment. [4]

4. A group of students plans to measure infiltration rates in two different land-use zones (forest vs. urban park).
Identify two controlled variables that must be kept constant to ensure the test is fair, and explain why controlling each is necessary. [4]

5. Distinguish between primary data and secondary data. Give one specific example of each that could be used in an investigation into traffic congestion in the CBD. [2]

Section B: Data Collection & Risk Assessment (15 Marks)

6. You are conducting a fieldwork investigation on beach profile changes.
Describe the correct method for measuring a beach profile using a clinometer, ranging poles, and a tape measure. [4]

7. Refer to the hypothetical scenario: Students are measuring water quality (pH and turbidity) in a slow-moving lowland river.
Identify two specific safety hazards associated with this fieldwork and propose a suitable risk mitigation strategy for each. [4]

8. Explain why pilot studies are considered an essential stage in the research design process. Provide two specific benefits a pilot study offers before the main data collection begins. [4]

9. A student uses a Likert Scale (1–5) to assess the aesthetic quality of buildings in an urban area.
Evaluate the reliability of this data collection method. [3]

10. When collecting sediment samples from a river bed, explain why it is important to take multiple subsamples at each site rather than a single stone. [2]

Section C: Data Presentation & Analysis (10 Marks)

11. You have collected data on pedestrian counts at 10 different locations in a city centre.
State the most appropriate graph type to present this data if you wish to show the spatial variation along a transect line. Justify your choice. [3]

12. A student calculates the mean and the median for a dataset of house prices in a district. The mean is significantly higher than the median.
Explain what this suggests about the distribution of the data and why the median might be a more representative measure of central tendency in this context. [3]

13. Describe one advantage of using Geographical Information Systems (GIS) over traditional paper maps for presenting fieldwork data. [2]

14. If a scatter graph shows a strong positive correlation between distance from the source and river velocity, does this prove causation? Explain your answer. [2]

Section D: Evaluation & Conclusion (10 Marks)

15. Define validity in the context of a geographical investigation. [1]

16. A student concludes that their hypothesis was "proven" because 80% of their data supported it.
Critique the use of the word "proven" in geographical science and suggest a more appropriate term. [2]

17. Explain how human error (e.g., misreading a clinometer) differs from systematic error (e.g., a tape measure that is stretched). Which type of error is more likely to affect the accuracy of the results? [3]

18. Suggest two ways in which the reliability of a fieldwork investigation into urban heat islands could be improved if the study were to be repeated. [2]

19. When writing the conclusion of a fieldwork report, why is it important to link findings back to geographical theory? [1]

20. Evaluate the limitations of using bi-polar evaluation (semantic differential) scales for measuring environmental quality in a diverse urban neighbourhood. [2]

Answers

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]