Design your method
A research question, a place, and a tension. That last one is more useful here than it looks: knowing what each side of the argument would want to see is how you work out what is worth measuring.
- A method a stranger could follow
- Enough planned data to answer your question
- Your variables, named and justified
- Safety and ethics specific to what you are doing
Your method is an instruction manual, written afterwards.
Two things at once, and students usually get one of them. It has to be complete enough for someone else to follow, and it has to be a record of what you actually did rather than a plan for what you intend to do. Anything you changed in the field belongs in it.
This criterion is two questions. Both must be yes.
Could a third party replicate your investigation from what you wrote, with you nowhere near them? If any step needs you standing there to explain it, the answer is no.
Does the method generate enough to answer the question you asked? Not enough data here hurts you again in steps 5 and 6, when there is nothing to find a pattern in.
Fail either and you are in the 1–2 band, however well the other one is done. There is no partial credit and no ladder of command terms here. It is unusually blunt for an IB criterion, and unusually easy to check.
Everything below is how we suggest you actually do it.
Write it as a record, not a plan
The guidance is explicit that the method should not be a proposal but an account of what was done. That means past tense throughout, and it means including the things that went differently from how you imagined them.
If you ran a pilot and changed your interval afterwards, say so. If the third site was inaccessible and you moved it, say so. Those are not admissions of failure; they are what makes the account true, and step 7 will thank you for them.
Standard protocols should be cited rather than copied out. Nobody needs the Winkler method reproduced in full; a reference to it is enough.
That caption is the model, and it is doing more work than it looks. A figure number your text can point at, what the picture shows, where it was taken and how high, which way you were facing, when, and whose photograph it is. All of it came off the phone: coordinates, altitude and bearing are stored in the image, and your photo library will show them.
Credit your own photographs, author's own photograph is the phrase, and cite anyone else's like any other source. A photograph nobody can locate or date is decoration, and decoration earns nothing. Note also what the picture cannot tell you: the interval between quadrats, and how the tape was oriented. Photographs support a written method, they do not replace one.
Plus correct scientific names for any organism. Vaccinium myrtillus, not bilberry.
For the grid reference and the map, use the national mapping service rather than a screenshot of Google Maps. Both of these give you coordinates for any point you click, a topographic base map worth reproducing, and historical layers if your issue is about how a place has changed.
- Border
- Orientation
- Legend
- Title
- Scale bar
And credit the basemap; that is not one of the five letters, and it is a formal requirement of its own.
How much data is enough
The mark scheme says "sufficient" and leaves you to work out what that means. It is not a mystery, though, because the statistics you will run in step 5 have their own thresholds, and those set the floor.
| How to lay the sampling out | Rule of thumb |
|---|---|
| Along a gradient | at least 5 intervals |
| Repeats at each point | at least 3 |
| Within each zone | 3 minimum, 5 better |
| Survey responses | at least 30 |
| Readings your chosen statistic wants | Per group |
|---|---|
| For a standard deviation | 5 or more |
| For a t-test | 10 or more |
| Before quoting a standard error | 30 or more |
Decide which test you will run before you go out. Discovering afterwards that you have eight readings and needed ten is a bad afternoon.
Fifteen quadrats on the ski piste and fifteen in the forest beside it. The question asks whether the two differ, so the statistic that answers it is a t-test, and fifteen clears the threshold of ten comfortably. That is why the comparison holds up.
It does not clear thirty, the number conventionally wanted before quoting a standard error of the mean. Standard error is what would let you say how precisely each site's own mean is known, and put honest error bars on it. So fifteen is enough to be confident the two sites differ, and not enough to be confident about either site's exact value.
Working that out beforehand would have meant sampling more, or planning around it. Found afterwards, it became an evaluation point in step 7 instead; the second-best outcome, because a specific, quantified limitation still earns marks there, but it is a weakness you are explaining rather than one you avoided.
Decide which statistic answers your question before you go out, then count backwards to how many readings it needs. Doing it in that order is the difference between a limitation you avoided and one you have to write about.
Measure the conditions, not just the thing
The IB does not require this. It asks for data appropriate to your question and leaves the rest to you. We ask for it anyway, and the reason is worth understanding rather than just complying with.
Measure only your organisms and you can report that two places differ. Measure the conditions as well and you can explain why they differ, which turns a correlation into a mechanism.
That mechanism is also the bridge back to step 3. A strategy acts on conditions: clearing, draining, grazing, building. If you have measured the conditions, you can say what the strategy would do. If you have not, your fieldwork and your argument sit side by side and never touch.
What is living there, and how much of it
The conditions that decide what can live there
The condition that actually mattered here was how much light reached the ground, because that is what grooming changes and what the plants respond to. The obvious instrument for it is a lux meter.
So light was measured with one: 12,000 lux on the piste against 5,000 in the forest. Two readings, taken at different moments under moving cloud. That is a number you can quote in a sentence and nothing more; there is nothing to correlate against diversity, and a cloud passing at the wrong moment could have reversed it.
The better approach was to measure canopy cover instead: the same underlying thing, but stable while you walk between plots. One reading per quadrat gives fifteen per site rather than one, so it can be plotted and correlated, and that correlation, rho = −0.77, turned out to be the strongest single piece of evidence in the whole study.
Measure the stable proxy for the condition rather than the condition at the moment you happened to be standing there. Ask of every abiotic variable: can I take one reading per quadrat, and will it still mean the same thing an hour later? If not, find the version that will.
The day itself
You will get less time in the field than you expect, and no second visit. The difference between a comfortable day and a wasted one is almost entirely what you settled before you left.
Which test you will run, and therefore how many readings you need. Where the sampling points go and how you will locate them. What each person is doing. Decisions made standing in the wind get made badly.
A blank notebook invites gaps. Print a table with a row per quadrat and a column per variable, so an empty cell is visibly a job rather than something you discover a week later.
The site from both ends, the apparatus in use, anything unusual, and any quadrat that surprises you. Photographs are outside the word count, and they are the only way to answer a question you have not thought of yet.
Do a pilot in the first ten minutes. Take one full set of readings at one point, then stop and look at it. Is the interval sensible? Is the variable actually varying? Is a reading taking three minutes when you have budgeted one? Changing your design after one point costs ten minutes; discovering the problem at the end costs the investigation. Whatever you change, write down that you changed it and why, step 7 pays for exactly that.
Record as you go, and record the awkward things too. The quadrat you moved because it landed on a path, the reading you repeated, the point you could not reach. Those notes are what makes the method an account rather than a plan, and they are where your specific limitations come from. Nobody reconstructs them afterwards.
One morning at Mijoux: thirty quadrats across two sites, percentage cover species by species, plus canopy cover, soil penetration depth and moisture at each one. The drone and ground photographs on this guide were taken twenty minutes apart on the same visit.
What it did not produce was a second chance. The lux-meter readings were abandoned as unusable, and the sample size turned out to be comfortable for a t-test and short for a standard error, both discovered afterwards, both now evaluation points rather than fixes.
Assume one visit. Before you go, write the list of numbers you must come home with; on the day, take a pilot set early and check it against that list. The things you cannot fix later are the sample size and the variables you did not think to measure.
Safety and ethics, about your investigation
No marks ride on a risk assessment any more, which has had an odd side effect: students either drop it entirely or paste in generic lab rules about tying back long hair. Neither helps.
What belongs here is what was actually risky about this work. Steep or uneven ground. Ticks. Working near water. Handling samples. And on the ethics side, what you did to leave the site as you found it, plus a consent form if people were involved.
One page is plenty. Say in the method that consent was obtained and how, then put a blank copy of the form in an appendix; that is the one thing an appendix is genuinely for. Never the completed ones: they carry other people's information, and an appendix is not read anyway.
Writing it in the future tense. "I will place five quadrats along each transect." It reads as a plan you might not have carried out, it hides everything you changed along the way, and it makes the account harder to trust. The fix takes ten minutes: go through and put the whole thing in the past tense, then add the two or three things that did not go as intended.
It can explain a technique you have not met before, what a Winkler titration measures, how a quadrat frame is used, as many times and as many ways as you need.
It cannot design the sampling. Where the quadrats go, how many, and at what interval are the decisions this criterion marks, and they depend on a place only you have stood in.
Ready for step 5?
0 of 10The first two are the criterion itself. The rest are how you get there.
Step 5 is where the good news arrives. Tables, graphs and calculations sit outside the word count entirely, so the six marks there cost you almost nothing to earn. Decide your statistical test now, before you go out, because it determines how much data you need to come back with.
The ski piste investigation used throughout this guide is a teaching reconstruction. The location, sampling design, plant records and soil data come from real fieldwork at Mijoux in the French Jura. Canopy cover measurements were added to illustrate good practice and were not part of the original fieldwork. Photographs are the author’s own, taken at the site.