This definitions covers Key Terms within Fieldwork Process and Enquiry for GCSE Geography. Revise Fieldwork Process and Enquiry in Fieldwork for GCSE Geography with 15 exam-style questions and 20 flashcards. This topic shows up very often in GCSE exams, so students should be able to explain it clearly, not just recognise the term. It is section 11 of 16 in this topic. Make sure you can use the exact wording confidently, because definition marks are often lost through vague language.
Topic position
Section 11 of 16
Practice
15 questions
Recall
20 flashcards
📖 Key Terms
enquiry — A structured investigation that begins with a geographical question or hypothesis, uses systematic evidence to test a prediction, and concludes with an honest evaluation of whether and how well the data answers the question. Fieldwork in geography is always framed as an enquiry, not a data-collection exercise.
hypothesis — A specific, testable prediction derived from geographical theory. It must be falsifiable — that is, it must be possible for the evidence to disprove it. A good hypothesis states what will change, in what direction, and why, with reference to a named geographical model or concept.
primary data — Information collected first-hand by the investigator during fieldwork. The collector controls the method, timing, location, and sample — but primary data collection is time-consuming and limited in scale by the time available in the field.
secondary data — Information collected by someone else and used as evidence within the enquiry. Secondary data enables historical comparison and access to large datasets but may not fit the exact study question and cannot be controlled by the investigator.
quantitative data — Numerical data that can be measured, counted, and analysed statistically. It reveals patterns and allows hypothesis testing, but it cannot explain why patterns exist on its own.
qualitative data — Descriptive or observational data that captures characteristics, opinions, and context. It adds explanation and human meaning to quantitative patterns, but it is harder to analyse statistically and may be subjective.
sampling — The strategy used to decide which data points to collect when measuring everything is impossible. The three main types are random (using random number selection), systematic (at regular intervals), and stratified (proportional representation of sub-groups).
reliability — The extent to which the same results would be obtained if the data collection were repeated using the same method. Reliable data is consistent; unreliable data varies due to random error, inconsistent technique, or changing conditions.
validity — The extent to which the data actually measures what the enquiry question requires. Data can be reliable without being valid — for example, a float timing surface velocity reliably but not capturing mean channel velocity.
representativeness — The degree to which the sample accurately reflects the characteristics of the whole population or study area. A biased or small sample produces conclusions that cannot be generalised.
anomaly — A data value that does not fit the overall trend or pattern. Anomalies should be identified, mapped or noted, and explained with reference to local site conditions or possible measurement error — not simply ignored.
Spearman's rank correlation coefficient (rs) — A statistical test that measures the strength and direction of the relationship between two ranked datasets. Results range from −1 (perfect negative correlation) to +1 (perfect positive correlation). The closer to ±1, the stronger the relationship.