What this lesson teaches
I can plan a fieldwork investigation with a clear question that can be tested in the time and with the tools available.
Syllabus K229, Topic 1.3, Key Question 1. How to design fieldwork?
Make a guess
A group wants to study the question "Are parks good?" What is the biggest problem with this question?
- It is about parks, which are not part of Geography.
- It needs a bigger sample before it can be asked.
- It is too broad for evidence to answer.
- It should be answered with interviews, not counts.
Show the answer
It is too broad for evidence to answer.
"Good" is not defined, and the question names no place, people or measure. A fair inquiry says what will be measured, where, when and for whom.
A good inquiry says exactly what will be measured, where, when and for whom, before any data are collected.
Start with a question that evidence can answer. A textbook, news story or website may make you curious about parks, but asking whether parks are good is too broad. A better question is: among residents of this neighbourhood, how does distance from the park relate to weekly visits? Say how you will measure distance, and over what period you will count visits.
A hypothesis is a prediction you can test. For example: residents who live farther from the park report fewer visits in the past seven days. It predicts a link between two variables, without claiming distance is the only cause.
Primary data are collected by you for your study. Secondary data already exist, such as a published map or population table. Quantitative data are numbers, such as distances or visit counts. Qualitative data describe experiences and meanings, such as why a route feels difficult.
You can use the two kinds of data in either order. Survey distances and visits first, then use interviews to explain a surprising result. Or start with interviews: if residents mention a dangerous crossing, a later survey can test how many people face that barrier.
Fit your aim, study area, sample size and timetable to your team, equipment and access. Use safe, approved sites and do not damage habitats. Taking part must be voluntary, and do not collect names or details you do not need. Run a small trial, called a pilot, to catch unclear questions or practical problems before collecting all your data.
- Hypothesis
- A testable prediction about two variables.
- Primary vs secondary
- Collected by you vs already published.
- Pilot
- A small trial run to fix problems first.
Step by step
Make it specific
Say who, where, when and what you will measure.
Choose the evidence
Numbers find patterns; accounts help explain them.
Test the method
A pilot checks wording, time, safety and consent.
Worked example: Improve the hypothesis
"People like parks" cannot be tested. "Residents farther from the park entrance report fewer visits in the past seven days" names two variables, a group and a time period.
Watch out for this
You must always collect numbers before interviews.
Either order works. A survey can find a pattern to explain, or interviews can suggest something to test.
Check your understanding
Which change makes a hypothesis easier to measure?
- Deciding the expected result before collecting any data.
- Replacing both variables with the word better, so it reads simply.
- Defining visits as the number in the last seven days.
Show the answer
Defining visits as the number in the last seven days.
Yes. A clear measure and time period make it testable.