Evaluation

Evaluation is the final stage of the geographical enquiry process, and it is arguably the most important for demonstrating your ability to think critically. Evaluation requires you to step back from your investigation and honestly assess its strengths, weaknesses, reliability and accuracy. It is not about saying "everything went well" — it is about showing that you understand what worked, what did not, and how the investigation could be improved.

Evaluation questions in the Edexcel B exam typically carry 4–8 marks and require extended writing. They are an opportunity to demonstrate higher-order thinking skills that distinguish top-grade answers from average ones.

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What Does Evaluation Involve?

Evaluation requires you to critically assess:

1. Data collection methods — Were they appropriate and effective?
2. Sampling strategy — Was the sample representative and unbiased?
3. Data quality — Was the data accurate, reliable and sufficient?
4. Presentation methods — Did the chosen graphs and maps effectively display the data?
5. Analytical techniques — Were the statistical methods appropriate?
6. Conclusions — Are they well-supported and trustworthy?
7. The investigation as a whole — What would you do differently?

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Evaluating Data Collection Methods

Strengths and Weaknesses of Common Methods

Method	Strengths	Weaknesses	Improvements
Tape measure for river width	Accurate to 0.01m; easy to use; consistent	Can sag if not held taut; difficult in wide/deep rivers	Use a laser rangefinder; have two people hold the tape tightly
Float method for velocity	Cheap; simple; quick	Only measures surface velocity; affected by wind; float can get stuck	Use a digital flow meter; apply the 0.85 correction factor
Flow meter for velocity	Accurate; measures at correct depth; digital readout	Expensive; can malfunction in shallow water; needs calibration	Take multiple readings; calibrate before use; have a backup float
Ruler for pebble size	Simple; quick; widely available	Only measures one dimension; difficult for irregular shapes	Use callipers for more precision; measure along the long axis consistently
Clinometer for beach profile	Gives precise angle measurements; standard method	Requires two people; can be affected by wind; parallax error	Take multiple readings; use a digital clinometer; practise technique
Questionnaire surveys	Direct opinions from people; can target specific questions	Response bias; social desirability; limited sample	Increase sample size; use random sampling of respondents; pilot test
Environmental quality survey	Quick; covers multiple factors; numerical output	Subjective; different observers may score differently	Standardise criteria; use the same observer; agree scores as a group

Exam Tip: When evaluating a data collection method, always use the three-part structure: (1) strength of the method, (2) weakness or limitation, (3) improvement you would make. This demonstrates balanced, critical thinking that examiners reward.

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Evaluating Sampling Strategy

Key Questions to Ask

Question	Good Practice	Poor Practice
Was the sampling method appropriate?	Systematic sampling for a transect (to show gradient)	Random sampling for a transect (may miss the gradient)
Was the sample size large enough?	30+ pebbles per site; 10+ survey sites	5 pebbles per site; 3 survey sites
Was the sample representative?	Sites covered the full river course from source to mouth	All sites clustered in the middle course
Was bias minimised?	Eyes closed when selecting pebbles; every 5th person surveyed	Choosing the largest pebbles; only surveying people who looked friendly
Were there enough repetitions?	3 velocity readings averaged per site	1 velocity reading per site

Evaluating Sample Size

The trade-off between sample size and practicality is a key evaluation point:

graph LR
    A["Small Sample<br/>Quick to collect<br/>Less reliable<br/>May not be representative"] --> B["BALANCE"]
    C["Large Sample<br/>Time-consuming<br/>More reliable<br/>Better coverage"] --> B
    B --> D["Optimal Sample<br/>Large enough to be reliable<br/>Practical within time and resources"]

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Data Reliability

Reliability means that the results would be consistent if the investigation were repeated under the same conditions. Consider these factors:

Factor	How It Affects Reliability	How to Improve
Number of measurements	More measurements = more reliable mean values	Take 3–5 readings at each site and calculate the mean
Consistency of method	Different methods at different sites reduce comparability	Use the same method, equipment and person throughout
Weather conditions	Rain or wind during fieldwork may affect measurements	Record weather; repeat on a different day; acknowledge the limitation
Time of data collection	Human activity varies by time of day and day of week	Standardise timing; repeat at different times for comparison
Equipment precision	More precise equipment gives more reliable readings	Use the best available equipment; calibrate before use
Inter-observer variation	Different people may take different measurements	One person does all measurements of the same type

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Accuracy vs Precision

These terms are often confused but have distinct meanings in fieldwork evaluation:

Term	Definition	Example
Accuracy	How close a measurement is to the true value	A flow meter reading of 0.45 m/s when the true velocity is 0.44 m/s — high accuracy
Precision	How close repeated measurements are to each other	Three readings of 0.44, 0.45, 0.44 m/s — high precision