How to write the IB Biology IA

The Biology IA is the one piece of coursework your Biology grade is marked on internally — worth 20% of your final grade at both SL and HL. Most students lose marks not because they can't do biology, but because they pick a question that produces no real data to analyse, or they never learn what each marking criterion actually rewards. Living things vary, and that variability is the heart of the subject: a strong Biology IA embraces it with replicates, means, standard deviation and a statistical test, rather than pretending it away. This guide walks you through the whole thing: what the IA is, how it's marked, exactly how to write each part, and what separates a top-band investigation from an average one.

Before you touch an organism, it helps to understand why the IA is built the way it is. The four criteria reward the full arc of a scientific investigation — designing it, analysing what came out, drawing a defensible conclusion, and judging honestly how far you can trust it. Because they are equally weighted, a beautiful experiment with a careless evaluation scores no better than a modest experiment evaluated brilliantly. The students who do best treat all four criteria as deliverables from the very first planning session, rather than rushing the design and hoping the analysis rescues them. Plan backwards from the graph and the statistical test you intend to produce, and you will almost always design a stronger investigation than someone who plans forwards from "an interesting idea".

The IB Biology IA at a glance

Under the current syllabus (first assessment 2025) the Biology IA is called the Scientific Investigation: a single, focused, individual investigation reported concisely — typically 6–12 pages within the 3,000-word guideline. It is marked out of 24 across four equally weighted criteria, and the same four criteria are used for Chemistry, Physics and Environmental Systems & Societies. There is no separate mark for "personal engagement" any more — your engagement should show through the relevance and ownership of your investigation. What distinguishes Biology from its sister subjects is the central role of biological variability: because no two organisms respond identically, the examiner expects to see enough replicate data for the variation to be quantified and tested for significance, not glossed over.

How the Biology IA is marked: the four criteria

Every mark comes from one of these four criteria, each worth 6. Write your IA criterion by criterion and check what each rewards:

How to write a Biology IA, step by step

1. Choose an organism or system and a focused research question. Pick a living system with one variable you can change over a range and one biological response you can measure. Phrase it: "How does [independent variable, range + units] affect [dependent variable, how measured] in [named organism]?"
2. State a null and alternative hypothesis. Write H₀ (no effect) and H₁ (the effect you predict) to be tested at α = 0.05, grounded in the underlying biology.
3. Plan sampling and standardisation. Decide your sample size, standardise organisms by age, size and source, and allocate them randomly to reduce bias.
4. Identify and control your variables. Name your control variables and explain, in prose, how each is held constant and how it would distort the response if it drifted.
5. Develop the method through preliminary trials. Use trials to fix concentrations, timings and ranges; report what you changed and why, and write a method another student could repeat.
6. Collect enough raw data. At least five values of the independent variable across a sensible range, each repeated at least three times (and ideally more for living material), recorded with units.
7. Process the data into mean and standard deviation. Calculate the mean and the standard deviation for every group so both the central value and the spread are visible.
8. Run an appropriate statistical test. Choose a t-test (two groups) or ANOVA (three or more), test at p < 0.05, report the test statistic and p-value, and decide whether to reject H₀.
9. Plot a graph with standard-deviation error bars. Plot the group means with SD error bars so variability and any overlap between groups are clear.
10. Write a justified conclusion. Answer the question, report the test outcome, then justify it against the biology and a referenced secondary value.
11. Evaluate honestly. Weigh limitations by impact, separate biological variability from systematic error, and propose specific improvements and an extension.

Biology IA structure: what goes in each section

There is no single mandated layout, but the clearest structure that maps onto the criteria is:

• Research question & background — the question, the biology behind it, and why it is worth investigating.
• Hypotheses — an explicit null (H₀) and alternative (H₁), to be tested at α = 0.05.
• Variables — independent (range + units), dependent (how measured), and controlled (in prose).
• Sampling & standardisation — sample size, how organisms are standardised, and random allocation.
• Method — a reproducible procedure, with safety and ethical handling where living things are involved.
• Raw data — a clear table with units, plus qualitative observations.
• Data processing — mean and standard deviation per group, with a worked sample calculation.
• Statistical test & graph — a t-test or ANOVA with a decision at p < 0.05, and a graph of means with SD error bars.
• Conclusion — answer, test outcome, justification against the biology and secondary data.
• Evaluation — limitations by impact, variability vs systematic error, improvements, extension.
• References — a consistent citation style throughout.

How to choose a research question that scores

More Biology IAs are decided at the question stage than at any other point, so it is worth slowing down here. A scoring question has four properties, and you should be able to point to each one before you commit. First, it centres on a genuine biological process you can manipulate — enzyme activity, growth, germination, photosynthesis, respiration, transpiration, membrane permeability or a behavioural response — rather than a purely physical or chemical change with no living system behind it. Second, it has a measurable, repeatable response: a length, a mass change, a rate, a count or an index that you can record to a sensible precision and reproduce. Third, it generates enough data for a statistical test; if you cannot picture at least five levels of your independent variable, each with several replicates, the question will not stretch into the top band of Data analysis. Fourth, it is feasible with school apparatus and within your time budget — an investigation you cannot finish, or that needs equipment you do not have, is a worse choice than a humbler question you can execute fully.

A reliable way to pressure-test a question is to write it in the form "How does [independent variable, with range and units] affect [dependent variable, with how it is measured] in [named organism]?" and then ask whether you could draw the predicted graph from memory. If you can sketch the expected trend and say why the biology produces it, the question is probably strong. If the trend is a shrug, narrow it: name the organism, fix the range, and decide exactly how the response will be measured. Avoid questions that compare named commercial products without a controllable variable behind them, questions that depend on a single dramatic result rather than a trend, and questions so broad that your replicates would be spread too thin to test. The narrower and more concrete your question, the easier every later section becomes.

What a strong vs weak Biology IA looks like

The fastest way to lift your marks is to see the difference. Here is the same work done two ways.

The research question

The statistics

The evaluation

Common mistakes that cost marks

• No real biological response. A question with no living system you can measure repeatedly is not a valid Biology IA.
• Too few replicates. Without enough repeats per level, a mean and standard deviation are meaningless and no statistical test is possible.
• No hypothesis. Missing an explicit H₀ and H₁ caps Research design and leaves the statistics with nothing to test.
• Descriptive statistics only. Means without standard deviation, and trends without an inferential test, cap Data analysis.
• Graph with no error bars. Error bars show the variability that defines the whole subject — leaving them off loses easy marks.
• No literature comparison. A conclusion that never compares to accepted biology can't reach the top band.
• "Human error." Examiners read this as "I didn't analyse my method." Always name a specific, real weakness and weigh its impact.
• Going over 3,000 words. Examiners stop reading at the limit — be concise.

Biology IA — frequently asked questions

Managing the 3,000-word limit

The word count is a guideline, not a wall, but examiners are explicit that they stop reading at the limit — so anything past 3,000 words simply will not be marked. The skill is spending words where they earn marks. As a rough budget, give your introduction and research question around 350–450 words, your variables and method around 600–700, your data processing and statistical analysis the largest share at roughly 700–900, your conclusion around 350–450, and your evaluation around 450–600. Raw-data tables, calculations, graphs and references generally sit outside the word count, so push detail into well-labelled tables and figures rather than narrating every number in prose. Cut anything that reads like a textbook recap of biology the examiner already knows; the marks are for your design, your analysis and your judgement, not for a literature review. If you find yourself over the limit, the fastest savings almost always come from trimming background theory and tightening the method, not from cutting analysis.

One more discipline pays off here: write in the third person and the past tense throughout, because that is how a scientific report reads and it keeps the prose lean. Replace "I think the seedlings probably grew less because…" with "Mean root length decreased with salinity, consistent with osmotic stress reducing water uptake." The second version is shorter, more confident and more obviously a piece of analysis — exactly what the conclusion and evaluation criteria reward.

Guidance written by experienced IB examiners and aligned to the current Biology guide (first assessment 2025). Not affiliated with or endorsed by the International Baccalaureate Organization.