A Level H1 Geography Fieldwork Quiz

A-Level Geography H1 Quiz - Fieldwork (Answer Key)

Total Marks: 40

Section A: Research Design and Hypothesis Formulation

1. Formulate a clear, testable hypothesis.

• Answer: Example: "Air temperature decreases as distance from the city center increases." OR "Vegetation cover is higher in the northern section of the park compared to the southern section."
• Marking: 1 mark for identifying variables, 1 mark for stating a directional relationship (testable).

2. Distinguish between null and alternative hypothesis.

• Answer:
  • Null Hypothesis: States that there is no significant relationship or difference between variables (e.g., "Distance from road has no effect on noise levels").
  • Alternative Hypothesis: States that there is a significant relationship or difference (e.g., "Noise levels decrease as distance from the road increases").
• Marking: 1 mark for each correct definition/distinction.

3. Identify independent and dependent variables.

• Answer:
  • Independent Variable: Distance from the main road.
  • Dependent Variable: Noise levels (decibels).
• Marking: 1 mark for each correct identification.

4. Importance of control variables + example.

• Answer:
  • Importance: To ensure that only the independent variable is affecting the dependent variable, establishing causality and fairness in the test.
  • Example: Time of day (for temperature/light), slope angle, or antecedent moisture conditions (for infiltration).
• Marking: 2 marks for explanation, 1 mark for valid example.

5. Critique and rewrite the aim.

• Answer:
  • Critique: "See if" is vague; "polluted" is subjective and undefined. It lacks specific parameters.
  • Rewrite: "To investigate the variation in dissolved oxygen levels and pH values at five sites along the Singapore River to assess water quality."
• Marking: 1 mark for critique, 2 marks for a specific, measurable rewrite.

Section B: Data Collection Methods and Sampling

6. Systematic sampling + advantage.

• Answer:
  • Description: Selecting samples at regular intervals (e.g., every 10 meters or every 5th house).
  • Advantage: Ensures even coverage of the study area/transect, reducing bias that might occur in random sampling (which might cluster in one area). It captures trends/changes effectively.
• Marking: 1 mark for description, 2 marks for advantage linked to transects/trends.

7. Pedestrian count reliability steps.

• Answer:
  1. Conduct counts at the same time of day/day of the week to control for temporal variations.
  2. Use multiple counters or repeat counts to calculate an average, reducing human error.
  3. Define clearly what counts as a "pedestrian" (e.g., excluding cyclists).
• Marking: 1 mark per valid procedural step (max 3).

8. Limitations of float method for river velocity.

• Answer:
  1. Wind can affect the speed of the float, leading to inaccurate surface velocity readings.
  2. The float only measures surface velocity, which is faster than the average velocity of the whole column.
  3. Human reaction time with the stopwatch introduces error.
• Marking: 1 mark per valid limitation (max 2).

9. Informed consent and anonymity.

• Answer:
  • Informed Consent: Participants must know the purpose of the study and agree to participate voluntarily.
  • Anonymity: Protects participants' privacy, encouraging honest answers and adhering to ethical guidelines.
• Marking: 1 mark for each explanation.

10. Primary vs. Secondary data + advantage of secondary.

• Answer:
  • Primary: Data collected firsthand by students (e.g., surveys, measurements).
  • Secondary: Data collected by others (e.g., census data, historical maps).
  • Advantage of Secondary: Saves time and resources; allows for analysis of long-term trends or large-scale patterns that students cannot collect themselves.
• Marking: 1 mark for distinction, 2 marks for advantage.

Section C: Data Presentation and Analysis

11. Graphical method for land use types.

• Answer:
  • Method: Divided bar chart or pie chart (for overall proportion) OR Land use transect diagram.
  • Justification: Categorical data (nominal) is best shown by proportions. A transect diagram shows spatial change along the line.
• Marking: 1 mark for method, 1 mark for justification.

12. Purpose of mean and standard deviation.

• Answer:
  • Mean: Provides a measure of central tendency (average value) to summarize the dataset.
  • Standard Deviation: Measures the spread or dispersion of data around the mean. A low SD indicates consistent/reliable data; a high SD indicates high variability.
• Marking: 1 mark for mean, 2 marks for standard deviation explanation.

13. Weak negative correlation implication.

• Answer:
  • As distance from the city center increases, building height generally tends to decrease.
  • "Weak" implies that other factors (e.g., local planning zones, topography) also influence building height, so the relationship is not strict.
• Marking: 1 mark for direction, 1 mark for interpreting "weak".

14. Essential features of a river cross-section.

• Answer:
  1. Title.
  2. Axes labeled with units (Width in m, Depth in m).
  3. Accurate scale (vertical and horizontal).
  4. Key/Legend for features (e.g., water level, bank type).
• Marking: 1 mark per feature (max 3).

15. Importance of annotating photographs.

• Answer:
  • Importance: Provides context and links visual evidence to geographical concepts/data.
  • Information: Location/Direction (North arrow), Date/Time, specific features identified (e.g., "erosion on outer bend").
• Marking: 1 mark for importance, 1 mark for examples.

Section D: Evaluation and Conclusion

16. Critique of "proven".

• Answer:
  • Critique: In science/geography, hypotheses are rarely "proven" absolutely due to potential errors, limited sample sizes, or changing conditions.
  • Alternative Term: "Supported," "Accepted," or "Not rejected."
• Marking: 1 mark for critique, 1 mark for alternative term.

17. Liebert scales: Strength and Weakness.

• Answer:
  • Strength: Easy to quantify and analyze statistically; allows for comparison between respondents.
  • Weakness: Subjective (one person's "5" is another's "4"); lacks detailed qualitative explanation of why they feel that way.
• Marking: 1 mark for strength, 2 marks for weakness explanation.

18. Validity of dry season data for flood risk.

• Answer:
  • Effect: Reduces validity significantly. Flood risk is highest during wet seasons/monsoons. Data from the dry season does not represent the extreme conditions that cause flooding, leading to an underestimation of risk.
• Marking: 2 marks for explaining the mismatch between data context and conclusion.

19. Improving reliability.

• Answer:
  1. Increase sample size (more sites/respondents).
  2. Repeat measurements at each site and calculate an average.
  3. Use more precise instruments (e.g., digital flow meter instead of float).
• Marking: 1 mark per valid suggestion (max 2).

20. Extent of agreement: Fieldwork limitations.

• Answer:
  • Agreement: Primary data is time-consuming, expensive, and limited in spatial/temporal scope. Weather and access issues can compromise data.
  • Disagreement/Nuance: Fieldwork provides authentic, localized understanding that secondary data cannot. It develops practical skills.
  • Synthesis: Best approach is a mixed-methods strategy: use secondary data for broad context and primary fieldwork for specific, detailed verification. Fieldwork is essential but must be scoped realistically.
• Marking:
  • 1 mark for acknowledging limitations.
  • 1 mark for acknowledging benefits.
  • 2 marks for a balanced conclusion/synthesis.