How do you analyse and evaluate fieldwork techniques and the data they produce?
Evaluating fieldwork techniques: judging the reliability, accuracy and limitations of a method and its data, identifying sources of error and bias, and suggesting improvements.
How to analyse and evaluate fieldwork techniques in SQA Advanced Higher Geography: judging the reliability, accuracy and limitations of a method and its data, identifying sources of error and bias, and suggesting improvements to strengthen an investigation.
Reviewed by: AI editorial process; not yet individually human-reviewed
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What this key area is asking
Gathering data is only half the skill; the spec asks for the analysis and evaluation of the data a technique produces. Evaluation means judging the reliability, accuracy and limitations of a method, identifying sources of error and bias, and suggesting improvements. The 10-mark gathering and processing section, and the geographical study, both reward this critical judgement, because conclusions are only as strong as the data behind them.
Reliability, accuracy and validity
These three ideas frame any evaluation. Reliability is improved by repeats and standard methods; accuracy by careful, calibrated measurement; validity by choosing a technique that genuinely captures the aim. Naming which is at stake makes an evaluation precise.
- Reliability. Consistency on repetition; improved by repeats and standard procedure.
- Accuracy. Closeness to the true value; improved by calibration and care.
- Validity. Measuring the right thing; improved by matching technique to aim.
Sources of error and bias
Typical weaknesses include subjective scoring (different observers disagree), small or biased samples, one-off timing (unusual weather or footfall), observer bias, and instrument or reading error. A strong evaluation names the specific weakness for the technique used, not a generic flaw.
A routine for evaluating a technique
- Identify the weaknesses. Name the specific sources of error and bias for this technique.
- Explain the effect. Say how each weakness distorts the data.
- Suggest improvements. Give concrete fixes (more observers, larger sample, repeats, calibration).
- Judge the conclusions. State how far the data supports the conclusions, given its reliability and validity.
Examples in context
Try this
Q1. What is the difference between reliability and validity? [2 marks]
- Cue. Reliability is consistency on repetition; validity is whether the technique measures what the aim intends.
Q2. Name two improvements that increase the reliability of a subjective survey. [2 marks]
- Cue. Any two of: several observers, a larger or stratified sample, repeat visits at matched times, a clear scoring scale.
Exam-style practice questions
Practice questions written in the style of SQA exam questions on this dot point, with worked answer explainers. The year tag is the paper they imitate, not the source.
SQA AH gathering5 marksEvaluate the reliability of a named fieldwork technique and suggest how the data could be improved.Show worked answer →
Evaluation judges how trustworthy the data is and why. Take a named technique (for example an environmental quality survey) and assess its reliability: scoring is subjective, so one observer may judge differently from another, and a single visit may catch unusual conditions. Accuracy depends on the instrument and the care of measurement.
A full answer identifies specific sources of error and bias (subjective scoring, small or biased sample, one-off timing, instrument error), explains their effect on the data, and suggests concrete improvements (several observers, larger or stratified sample, repeat visits at matched times, calibrated instruments). The strongest answers link reliability to whether the conclusions can be trusted.
SQA AH gathering4 marksExplain the difference between the reliability and the validity of fieldwork data, with an example of each.Show worked answer →
Reliability is consistency: would the same method give the same result if repeated? Validity is whether the technique actually measures what the aim intends. A method can be reliable but not valid, and the reverse.
Strong answers define both, give an example of each (reliability: repeated stream-velocity readings agreeing; validity: a questionnaire whose questions genuinely capture shopping behaviour rather than something else), and explain how to improve each: repeats and standard methods for reliability, well-targeted questions and techniques for validity. They note that conclusions are only as strong as the reliability and validity of the data.
Related dot points
- Designing research and fieldwork: setting aims and hypotheses, choosing appropriate primary and secondary techniques, planning a sampling strategy and location, and piloting before collecting data.
How to design a research and fieldwork methodology in SQA Advanced Higher Geography: setting clear aims and hypotheses, selecting appropriate primary and secondary techniques, planning a sampling strategy and a suitable location, and piloting methods before collecting data.
- Physical fieldwork techniques: beach profile, micro-climate, pebble, slope, soil, stream and vegetation analysis, including the equipment, the measurements taken and what each technique reveals.
The examinable physical fieldwork techniques in SQA Advanced Higher Geography: beach profile, micro-climate, pebble, slope, soil, stream and vegetation analysis. Covers the equipment, the measurements taken, and what each technique reveals about the physical environment.
- Human fieldwork techniques: environmental quality survey, pedestrian and traffic surveys, perception studies, and urban and rural land use mapping, including how each is conducted and what it reveals.
The examinable human fieldwork techniques in SQA Advanced Higher Geography: environmental quality survey, pedestrian survey, traffic survey, perception studies, and urban and rural land use mapping. Covers how each is conducted and what it reveals about the human environment.
- Questionnaire and interview design and implementation: writing clear unbiased questions, choosing open and closed formats, sampling respondents, and conducting interviews to gather reliable primary data.
How to design and implement questionnaires and interviews in SQA Advanced Higher Geography: writing clear, unbiased questions, choosing open and closed formats, sampling respondents fairly, and conducting interviews to gather reliable primary data for analysis.
- Correlation tests: Spearman's rank correlation for ranked data and Pearson's product moment correlation coefficient for interval data, interpreting the coefficient and its significance.
How to use the two correlation tests in SQA Advanced Higher Geography: Spearman's rank correlation coefficient for ranked data and Pearson's product moment correlation coefficient for interval data, including interpreting the coefficient between minus 1 and plus 1 and judging significance.
Sources & how we know this
- Advanced Higher Geography Course Specification — SQA (2019)
- Advanced Higher Geography Specimen Question Paper — SQA (2019)