Common Misconceptions
Part of Fieldwork Process and Enquiry — GCSE Geography
This common misconceptions covers Common Misconceptions 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 12 of 16 in this topic. Use this common misconceptions to connect the idea to the wider topic before moving on to questions and flashcards.
Topic position
Section 12 of 16
Practice
15 questions
Recall
20 flashcards
⚠️ Common Misconceptions
Misconception 1: "Random sampling means choosing randomly — just pick whatever you want"
Reality: Random sampling has a specific technical meaning in fieldwork — it means using a random number generator or random number table to select sample points, so that every possible point in the study area has an equal chance of being selected. "I picked pebbles at random" or "we asked people who were walking past" is not random sampling — it is opportunistic sampling, which is highly biased because it favours accessible or willing individuals. True random sampling removes human choice entirely from the selection process.
Misconception 2: "Primary data is always better than secondary data"
Reality: Both have genuine strengths and weaknesses, and the choice should depend on the enquiry question. Primary data is current, site-specific, and directly relevant — but it is limited in scale and affected by conditions on the day. Secondary data can cover decades of historical change, entire regions, or thousands of households — things impossible to survey in a single fieldwork trip. A strong investigation uses both and justifies why each was chosen. OCR B and AQA both reward students who can evaluate the appropriateness of their data sources, not just list them.
Misconception 3: "Evaluation just means listing everything that went wrong"
Reality: A strong evaluation assesses the overall quality of the investigation across three dimensions — reliability, validity, and representativeness. It acknowledges both strengths and limitations. It discusses whether the method was appropriate for the question, whether the sample was representative, and whether the results support the conclusion. Most critically, it offers specific, realistic improvements — not vague ones. "We could collect more data" earns no marks. "Using stratified sampling across different times of day would have reduced temporal bias in the pedestrian count and produced a more representative sample of the study area's users" earns marks at the highest level.