AQA · A-Level · Geography
Course version: 7037 · Version from Sept 2018
Understand the nature and use of different types of geographical…
Full specification wording
Geographical skills checklist: understand the nature and use of different types of geographical information, including qualitative and quantitative data, primary and secondary data, images, factual text and discursive/creative material, digital data, numerical and spatial data and other forms of data, including crowd-sourced and 'big data'
Geographical investigations rely on diverse data types.
Checked against the AQA 7037 specification (opens in a new tab) on .
- 4 key terms
Study notes
From the checked teaching notes for this specification point.
The idea
Geographical investigations rely on diverse data types. Quantitative (numerical) data, like river velocity in m s⁻¹, and qualitative data, such as interview transcripts, offer different insights. Primary data is collected firsthand, while secondary data uses existing sources like census records. Geographers must evaluate images (photographs, satellite), factual texts (government reports), and discursive/creative materials (poems, artwork) to understand place meaning. Digital and spatial data, often mapped using GIS, reveal geographical patterns. Modern research increasingly utilises crowd-sourced information (e.g., participatory mapping) and 'big data' (massive datasets like mobile phone tracking) to analyse complex spatial trends.
What earns the marks
- Define and distinguish between primary (firsthand collection) and secondary (pre-existing) data sources.
- Evaluate the reliability and subjectivity of qualitative sources, including discursive/creative materials and images.
- Explain the role of quantitative, numerical, and spatial data in identifying objective geographical patterns.
- Assess the advantages and ethical considerations of using crowd-sourced information and 'big data' in geographical research.
Common mistakes and how to put them right
Assuming quantitative data is entirely objective.
Put it right: Recognise that numerical data collection methods and sampling strategies can introduce bias.
Dismissing discursive or creative materials as geographically useless.
Put it right: Use poems, art, and literature to evaluate lived experiences and sense of place.
Confusing crowd-sourced data with big data.
Put it right: Understand that crowd-sourced data is actively contributed by the public, whereas big data refers to massive, often passively collected datasets.
Exam tips
- When evaluating a data source, explicitly state whether it is primary or secondary, and qualitative or quantitative.
- Use specific examples of 'big data', such as Oyster card tap-ins or GPS tracking, to illustrate modern spatial analysis.
- Critically assess the provenance of factual texts and images, noting the author's purpose and potential bias.
Try the lesson
The start of the Geographical skills checklist: understand the nature and use of different types of geographical information, including qualitative and quantitative data, primary and secondary data, images, factual text and discursive/creative material, digital data, numerical and spatial data and other forms of data, including crowd-sourced and 'big data' lesson, made from checked teaching notes for this specification point.
Have a go first
A student conducts a pedestrian count in a town centre to investigate footfall. Which classification best describes this type of geographical data?
Listen
Geographical investigations rely on diverse data types. Quantitative (numerical) data, like river velocity in m s⁻¹, and qualitative data, such as interview transcripts, offer different insights. Primary data is collected firsthand, while secondary data uses existing sources like census records. Geographers must evaluate images (photographs, satellite), factual texts (government reports), and discursive/creative materials (poems, artwork) to understand place meaning. Digital and spatial data, often mapped using GIS, reveal geographical patterns. Modern research increasingly utilises crowd-sourced information (e.g., participatory mapping) and 'big data' (massive datasets like mobile phone tracking) to analyse complex spatial trends. A strong answer earns marks for these points. Define and distinguish between primary (firsthand collection) and secondary (pre-existing) data sources. Evaluate the reliability and subjectivity of qualitative sources, including discursive/creative materials and images. Explain the role of quantitative, numerical, and spatial data in identifying objective geographical patterns. Assess the advantages and ethical considerations of using crowd-sourced information and 'big data' in geographical research. A common slip: Assuming quantitative data is entirely objective. Instead, recognise that numerical data collection methods and sampling strategies can introduce bias. Exam tip: When evaluating a data source, explicitly state whether it is primary or secondary, and qualitative or quantitative.
See it
Key words
Say what each word means before you turn the card.
Primary data
Try answering aloud or in your head before turning the card.
Secondary data
Try answering aloud or in your head before turning the card.
Qualitative data
Try answering aloud or in your head before turning the card.
Quantitative data
Try answering aloud or in your head before turning the card.
See every definition
- Primary data
- Data that is collected firsthand rather than taken from existing sources.
- Secondary data
- Data that uses existing sources, such as census records, rather than being collected firsthand.
- Qualitative data
- Non-numerical information, such as interview transcripts, that offers different insights from numerical data.
- Quantitative data
- Numerical data, like river velocity in m s⁻¹, that offers different insights from non-numerical information.
Label the diagram
Some boxes have lost their names. Pick the right name for each number.
1Box 1
2Box 2
3Box 3
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