Fieldwork Planning and Data Collection

Start with a question that evidence can answer

A geographical enquiry investigates a question about places, patterns or processes. Planning begins by deciding what you want to find out, then choosing evidence that will help answer it. Collecting everything that happens to be easy to measure can leave you with plenty of data but little relevant information.

An aim states what the investigation is trying to achieve. An enquiry question expresses this as a question, while a hypothesis is a testable statement predicting an outcome. For example, an aim could be to investigate differences in environmental quality around a regenerated urban area. A possible question is: ‘How does environmental quality vary between regenerated and nearby non-regenerated sites?’ A hypothesis might predict that environmental quality is higher at the regenerated sites. These are possible enquiry designs, not findings about a particular place.

A suitable question or hypothesis needs to be:

• Geographical: linked to a concept or process studied in geography.
• Focused and measurable: clear about what will be investigated and what evidence could answer it.
• Manageable: achievable with the available time, equipment and number of people.
• Practical and safe: suitable locations must be accessible, with risks that can be controlled.

‘Is this town good?’ is too vague because ‘good’ could mean many things. A question about differences in environmental quality is more focused, provided you define the indicators you will assess.

Connect the enquiry to geographical understanding

The geographical concept explains why the question matters and helps you decide what to measure. An enquiry does not have to test a named theory or model, but it must investigate an identifiable geographical concept or process from the course.

For example, a river investigation could explore changes in channel characteristics, using measurements of width, depth or velocity. A regeneration enquiry could explore how investment in an urban area relates to its environmental quality, use and people's perceptions.

These connections guide data selection. Pedestrian counts can indicate how much a regenerated area is being used, so they may help investigate its success. However, a busy place is not necessarily a place where everyone is satisfied. Questionnaire responses can add information about people's views. Different methods can therefore answer different parts of the same question.

Choose locations and evidence together

A useful fieldwork location must be safe, accessible and able to provide relevant information. A convenient site is not automatically a suitable one.

To compare regenerated and non-regenerated environments, you need access to both types of site. To investigate change across a river channel, you need a location where measurements can be made safely across the channel. The location and method must work together: a site is unsuitable if the required evidence cannot be collected there safely.

Primary data are original data collected first-hand for the investigation. Examples include your group's river measurements, pedestrian counts, questionnaire responses and photographs. Each GCSE fieldwork enquiry must include at least one primary data collection method.

Secondary data come from existing sources. Census results can provide population information; maps can help identify locations; older photographs can provide evidence of earlier conditions; and council documents or newspaper reports can help explain why regeneration took place. Secondary data can support an enquiry, but using them is not compulsory in every enquiry.

Check whether secondary evidence fits your purpose. Its date, geographical coverage, original collection method and possible bias all matter. Older information may be unsuitable for describing current conditions but useful for investigating change. Primary data also need careful collection: being first-hand does not automatically make them accurate or representative.

Select physical and human data that answer the question

Physical data describe the natural environment, such as river depth or plant cover. Human data describe people, activities and built environments, such as pedestrian numbers, opinions or environmental quality in an urban area. Across your fieldwork, you encounter both physical and human geography; every individual enquiry does not need to collect every type of data.

A second distinction is between quantitative and qualitative data. Quantitative data are numerical, such as a depth measurement or a count. Qualitative data describe features or experiences, such as an interview answer or an annotated photograph. Either type can be primary or secondary.

An environmental quality survey illustrates why these distinctions matter. Observers judge indicators such as litter or noise using an agreed numerical scale. The resulting scores are quantitative, but the judgements remain subjective. Clear scoring criteria and discussion between observers help make scoring more consistent. Numbers alone do not make a method objective.

Sample rather than trying to measure everything

A sample is a selection from the population or area you want to investigate. Sampling is usually necessary because time, equipment and access are limited. The aim is to collect enough relevant evidence to represent the places or people being studied without making the investigation unmanageable.

For random sampling of an area, you can number eligible grid squares and use a random number generator to select them. Choosing whichever sites look easiest is not random sampling.

For systematic river-depth sampling, a tape measure across the channel provides a reference line. Depth readings taken every 50 cm give regularly spaced measurements rather than measurements only at apparently deep points. This is a concrete example of how sampling supports an enquiry into channel shape.

For a questionnaire, stratification might ensure that different age groups are represented. If the aim is to represent the population as a whole, sample groups in proportion to their population sizes where those proportions are known. If the aim is to compare groups, an equal number from each may be useful, but that sample is not necessarily proportional to the whole population. Random or systematic selection can also be used within the groups.

There is no single sample size suitable for every enquiry. Consider the variation in the study area, the groups that need representation, available time and the accuracy required. More observations can improve coverage, but collecting more data does not remove a biased method or repeated measurement error.

Measure and record consistently

A method needs both a clear procedure and a reason for using it. Before fieldwork, decide what equipment is needed, where and when measurements will be taken, and how results will be recorded.

For river depth, a tape measure and a graduated ruler or measuring pole allow you to record distance across the channel and depth at each sampling point. Use consistent units and the same measuring procedure at each point. A recording sheet should include the site, date, distance across the channel and depth. Collecting these paired measurements makes the data relevant to channel shape, rather than producing an unlocated list of depths.

For pedestrian counts, define a counting point or boundary, tally people crossing it, and use the same counting duration at each site. Record the location, date, time and duration alongside the count. Comparable timings matter because differences in counts might otherwise reflect different observation periods rather than differences between sites.

For questionnaires, use consistent questions and a planned sampling strategy. Closed questions provide answers that are easier to compare, while open questions allow people to explain their views. Questions should be clear and neutral rather than encouraging a preferred answer. Explain the purpose, ask whether the person is willing to participate and respect refusal.

For an environmental quality survey, use the same indicators, scoring scale and criteria at every site. Record individual indicator scores as well as the location. This keeps the evidence traceable and helps ensure that sites are being assessed on the same basis.

Design recording sheets before collecting data, with clear headings, units and space for relevant observations. A small trial can reveal unclear questions, impractical sampling intervals or missing columns before the main collection begins.

Identify hazards and reduce risks

Risk assessment means identifying hazards, considering who could be harmed and how, deciding precautions, recording and implementing them, and reviewing the assessment if circumstances change.

Precautions should address the actual source of harm:

• Slippery river rocks: falls can cause injury. Wear suitable footwear with good grip and use only approved safe sampling locations.
• Heavy rainfall: rising water or flash flooding can make river work dangerous. Check forecasts and do not proceed when conditions are unsafe.
• Incoming tides: students can become cut off. Check tide times, monitor changing conditions and avoid routes that may become inaccessible.
• Traffic: students may be injured when crossing roads. Use safe crossing procedures and choose counting positions away from moving vehicles.
• Questionnaires with strangers: an approach may annoy or offend someone. Work in groups, explain the purpose politely, accept refusal and withdraw if someone becomes upset.

Safety can require changing the location or method, or stopping collection altogether. The best-designed enquiry is one that gathers relevant evidence without exposing people to unnecessary harm.

Plan the enquiry

Choose a focused, geographical and measurable question or hypothesis. Check time, equipment, access and safety. Link it to a geographical concept or process; a named model is not compulsory.

Locations must be safe, accessible and informative for the question.

Select relevant evidence

• Primary: collected first-hand for the enquiry; required in each enquiry.
• Secondary: existing evidence, such as census results, maps or earlier photographs; check date, coverage and suitability.
• Physical/human: what the data describe.
• Quantitative/qualitative: numerical or descriptive information.

Select data because they answer the question, not simply because they are easy to collect.

Choose sampling deliberately

• Random: equal chance of selection; reduces selection bias but may miss areas.
• Systematic: regular intervals; quick and evenly spaced but may miss variation.
• Stratified: samples from relevant groups; ensures coverage but requires justified group sizes.

Balance sample size and coverage against practical limits. A larger sample does not automatically remove bias.

Collect consistently and safely

Use consistent equipment, units, questions, scoring criteria and observation durations. Record locations, dates, times and relevant conditions alongside results.

Justify each choice by linking it to the evidence needed. Identify each hazard, explain possible harm and choose a precaution that reduces that specific .