Specific skills — AQA A-Level Geography
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Specific skills explained
A-level Geography demands the development of specific qualitative and quantitative skills, reflecting the diverse nature of geographical enquiry.
Read the full explanation
Quantitative skills involve numerical data, requiring you to calculate and analyse statistics, such as using standard deviation to assess variations in pebble size. Qualitative skills focus on non-numerical data, requiring you to interpret meaning and subjectivity, such as coding interview transcripts or analysing the representation of a place in media. You must actively develop proficiency in both domains, as modern geography relies on mixed-methods approaches. Examiners expect you to select, apply, and evaluate the most appropriate specific skills for different types of geographical data and research questions across the course.
Your focus
- Distinguish between specific qualitative and quantitative geographical skills.
- Demonstrate the development of quantitative skills through statistical and numerical analysis.
- Apply qualitative skills to interpret non-numerical geographical data and sources.
Specific skills exam tips
Examiner Tips
- 💡Create a revision table categorising all required skills into 'qualitative' and 'quantitative' to ensure balanced preparation.
- 💡When evaluating a geographical study or fieldwork, explicitly discuss the strengths and limitations of the specific qualitative or quantitative skills used.
- 💡Practice combining both skill types (mixed methods) in your NEA to provide a more comprehensive geographical analysis.
Common Mistakes
- Over-relying on quantitative data while neglecting qualitative analysis; correction: ensure equal focus on developing skills like textual analysis and interpreting subjective sources.
- Confusing qualitative and quantitative data types; correction: remember that quantitative is numerical and measurable, whereas qualitative is descriptive and interpretive.
- Failing to justify the choice of a specific skill; correction: always be prepared to explain why a particular qualitative or quantitative technique is the most appropriate for the data presented.