NEA

Topic 25: Analysis, conclusions, critical reflection and the wider context

Key ideas

• Analysis and interpretation:
  • Describe the patterns in your data, quoting figures.
  • Explain them with theory (link back to your literature review).
  • Identify anomalies and suggest reasons for them.
  • Use statistics to show significance.
  • Link qualitative evidence (e.g. interviews) to the quantitative findings.
• Conclusions:
  • Answer each sub-question and the main question directly.
  • State whether you accept or reject each hypothesis.
  • Support every claim with evidence from your results.
• Critical evaluation (this is where the top marks are):
  • Methods: were they accurate, reliable and valid? Consider sampling bias, the timing (one day, the season, the tide) and equipment limits.
  • Data: consider the sample size, outliers and how far the findings can be generalised.
  • Overall reliability of the conclusions: how confident are you?
  • Improvements and extensions: e.g. collect data across seasons or add more sites.
• The wider geographical context:
  • Relate your findings to larger scales and to theory, e.g. sediment cells, SMP policy, climate change and sea-level rise.
  • Show how your small study contributes to understanding the bigger picture.
  • Recognise the ethical and socio-political dimensions.

Qualitative data skills (from the outline's data-handling list)

• Using and understanding mixed methods, including interviews.
• Interpreting and evaluating source material:
  • Text and pictures.
  • Oral accounts, newspapers, creative media (e.g. art, film, poetry) and social media.
  • Aerial, oblique and ground photographs, sketches and drawings.
  • For each source, ask: who created it, why, when, for which audience, and what it omits.
• Limitations of qualitative techniques:
  • Small and unrepresentative samples.
  • Interviewer bias.
  • Subjective interpretation.
  • These shape the particular "representations" of places you produce.
• Ethical and socio-political implications:
  • Consent and anonymity.
  • Power relations, e.g. whose voices are heard.
  • The risk of stigmatising communities when representing deprivation.

Quantitative and geospatial skills

• What makes data geographical? It has a location (spatial reference) as well as an attribute.
• GIS (Geographic Information Systems) layer, analyse and present geo-located data.
  • Examples: Edina Digimap, ArcGIS Online, QGIS, Environment Agency flood maps, MAGIC (environmental designations) and LiDAR (DEFRA Survey Data Download).
  • Uses: buffer zones, overlays and change detection.
• Collecting digital geo-located data: GPS apps, geotagged photos and Survey123-type forms.
• Other skills to know: reading dot maps, kite diagrams, logarithmic scales, dispersion diagrams and satellite images.

Exam technique (fieldwork in the exams)

• The exams can ask about fieldwork and data in general.
• Practise:
  • "Explain one limitation of this sampling method" (3 marks).
  • "Calculate the IQR" (2 marks).
  • "Suggest how data presentation could be improved" (4 marks).

Self-test

Q1: Why is critical evaluation worth so many marks in the NEA? A: Mark area 4 (24 marks) rewards reflecting on the reliability and validity of methods and conclusions and placing them in the wider context. It shows geographical maturity rather than just reporting results.

Q2: Give two limitations of using social media posts as evidence about a place. A: They are unrepresentative (self-selecting users, often younger) and may be biased, exaggerated or curated. They are also hard to verify.

Q3: What makes data "geographical"? A: It is spatially referenced (it has a location), so patterns and relationships across space can be analysed.

Summer assessments: the Year 12 exam on Coasts and Water (teacher marked), then NEA data collection after half-term. Write-up and final submission (70 marks) follow in Year 13.

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