Found a topic you like?
Drop it straight into the free Biology IA frame. Research Design is free — unlock Data Analysis, Conclusion & Evaluation to finish the whole IA: data tables with standard deviation, graphs with error bars, a statistical test and a justified conclusion.
Start this IA in the Biology frame →ENZYMES
Enzyme studies give a clean rate, a clear optimum or saturation curve, and easy replicates — perfect for means, standard deviation and a statistical test.
1 · How does temperature affect the rate of catalase activity in potato (or liver)?
A textbook bell-shaped curve with a clear optimum and denaturation tail — ideal for an ANOVA across temperatures, with rich evaluation about tertiary-structure breakdown.
2 · How does substrate concentration affect the rate of an amylase-catalysed reaction?
Produces a saturation (Michaelis–Menten-style) curve you can explain through active-site occupancy — strong theory links and a quantitative rate to graph with error bars.
3 · How does pH affect the activity of pepsin (or catalase)?
A clear optimum to find and explain (charge changes at the active site) gives a genuinely interesting result — well above a generic "does it work" study.
PHOTOSYNTHESIS & RESPIRATION
Gas-exchange studies give a measurable rate and a clean dose–response — graphable, repeatable and easy to control.
4 · How does light intensity affect the rate of photosynthesis in pondweed (Elodea)?
A classic inverse-square relationship that plateaus at a limiting factor — clean trend, clear controls (temperature, CO₂) and a strong evaluation hook.
5 · How does sucrose concentration affect the rate of respiration in yeast?
Reliable, controllable and quantitative; a rate–concentration graph lets you discuss substrate limitation and link respiration to ATP yield in the conclusion.
6 · How does temperature affect the rate of fermentation (CO₂ release) in yeast?
An enzyme-controlled optimum with a denaturation drop-off — pairs an explainable trend with an ANOVA across temperatures.
TRANSPORT — OSMOSIS, DIFFUSION & TRANSPIRATION
Water-relations studies give precise mass or distance data and small uncertainties — examiner gold for processing.
7 · How does external salt (or sucrose) concentration affect mass change in potato tissue?
A clean straight-line trend that crosses zero at the cell's water potential — you can read off an isotonic point, giving a quantitative result above "it gets heavier".
8 · How does temperature affect the rate of diffusion of dye through agar?
Cheap, repeatable and quantitative; links the kinetic theory of diffusion to surface-area-to-volume ideas for a confident conclusion.
9 · How does wind speed (or humidity) affect the rate of transpiration in a leafy shoot?
A clear environmental dose–response with strong syllabus links to stomata and the transpiration stream — and an honest evaluation about uptake ≈ transpiration.
Ready to write it up properly?
The Biology IA frame walks you through every criterion — and the paid unlock builds your data tables, standard deviation, graphs with error bars and statistical test into one export-ready document.
Open the Biology IA frame →ECOLOGY & THE ENVIRONMENT
Fieldwork and microcosm studies generate genuinely variable data — exactly the situation a statistical test is designed for.
10 · How does light intensity affect the abundance of a plant species along a transect?
A real abiotic gradient with a clear ecological story; test the relationship with a Spearman's rank or chi-squared for a top-band analysis.
11 · How does soil moisture (or pH) affect the distribution of a chosen plant?
An abiotic factor mapped against a measurable biotic response — well suited to a chi-squared test of association and a referenced ecological conclusion.
12 · How does leaf-litter depth affect invertebrate abundance or diversity?
Calculating a diversity index is a step up in sophistication and gives a comparable, quantitative outcome with an ethical, catch-and-release method.
HUMAN PHYSIOLOGY & HEALTH
Non-invasive human studies give plenty of replicates and natural variability — ideal for a t-test or ANOVA when ethics are handled carefully.
13 · How does exercise intensity affect recovery heart rate?
Within-participant design controls for individual differences; a paired comparison and clear trend make for strong, ethical analysis (informed consent, PAR-Q screening).
14 · How does reaction time differ with sleep, time of day, or a distractor?
Lots of repeatable trials per person and an obvious two-group comparison — a clean t-test with anonymised data and consent.
15 · How does breath-holding after light exercise compare to rest?
Links to the control of ventilation by blood CO₂; a paired design and clear biological mechanism give a confident, referenced conclusion.
MICROBIOLOGY & PLANTS
Growth and germination studies give a real biological response over time — variable, repeatable and statistically rich.
16 · How does salt (NaCl) concentration affect germination and root growth of mung beans?
High biological variability is exactly what a one-way ANOVA is for; a clear salinity-stress gradient and easy replicates make this a reliable top-band investigation.
17 · How does a plant growth factor (light colour, gibberellin, or mineral) affect seedling growth?
A controllable growth response with a clear mechanism (photoreceptors, hormone action); processing into mean ± SD with error bars reaches the top of Data Analysis.
18 · How effective are different natural antibacterials (garlic, honey, herb extracts) against bacterial growth?
A real consumer/medical hook with a measurable, comparable outcome; safe with non-pathogenic cultures and an incubation temperature below 30 °C.
19 · How does pH affect the germination rate of cress (or radish) seeds?
Cheap, fast and repeatable; a clear optimum links to acid-rain relevance and supports a chi-squared or ANOVA comparison.
MORE EXAMINER-RANKED IDEAS
20 · How does substrate concentration affect the activity of immobilised (or fresh) catalase?
Generates a saturation curve that demonstrates active-site limitation — a sophisticated enzyme-kinetics story with clean, graphable data.
21 · How does CO₂ availability affect the rate of photosynthesis in pondweed?
Isolates a second limiting factor for a richer conclusion about how light and CO₂ interact — strong, controllable and quantitative.
22 · How does surface-area-to-volume ratio affect diffusion rate in agar blocks?
A precise, repeatable model of why cells stay small; the clean inverse relationship makes for confident processing and a clear biological conclusion.
23 · How does caffeine concentration affect the heart rate of Daphnia?
A clear dose–response with a stimulant mechanism; handle ethically (low concentrations, short exposure, recovery) for a strong, well-justified study.
24 · How does temperature affect membrane permeability in beetroot?
Quantitative absorbance data and a clear threshold where membranes break down — links phospholipid-bilayer theory to a measurable, graphable result.
From a topic to a top-band IA
An idea is the easy part — the marks are in how you build it. The Biology IA is scored out of 24 across four equal criteria: Research Design, Data Analysis, Conclusion and Evaluation. Whichever topic you pick, the same moves win: a focused research question with named variables, an explicit null and alternative hypothesis tested at α = 0.05, a method standardised through trials, replicate data processed into mean ± standard deviation, an appropriate statistical test (t-test, one-way ANOVA or correlation) correctly interpreted, a graph of means with error bars, a conclusion justified against the biology and secondary data, and an evaluation that separates biological variability from systematic error.
Build your chosen idea into a full IA
The examiner-written Biology IA writing frame takes you through every section with the rubric, worked examples and the traps that cost marks. Research Design is free — unlock Data Analysis, Conclusion & Evaluation to finish the whole investigation and export it to Word or PDF.
Open the Biology IA frame →Biology IA ideas — FAQ
What makes a good IB Biology IA topic?
A controllable biological process at its heart (enzyme activity, growth, germination, photosynthesis, respiration, transpiration or behaviour), a clearly named independent variable with range and units, a dependent variable with how it's measured, feasibility with school apparatus, and enough replicates to handle biological variability and run a statistical test. Phrase it as "How does … affect …?".
How many repeats and what sample size do I need?
At least five values of the independent variable, each with at least five replicates so a mean and standard deviation are meaningful — many strong IAs use ten or more. Living things vary, so more replicates tighten your error bars and increase the power of a t-test or ANOVA to detect a real effect. Standardise organisms by age, size and source and allocate them randomly.
Can I just copy one of these ideas?
Use them as a launchpad, but make the investigation your own: narrow the research question, choose your own organism and variable ranges, and standardise the method through your own trials. That ownership is exactly what the Research Design and Evaluation criteria reward.
How do I turn the idea into a top-band IA?
Build it section by section in the free Biology IA writing frame — research question, null and alternative hypothesis, variables, standardised method, replicate data with standard deviation, a statistical test, graphs with error bars, a conclusion against the biology, and an evaluation that separates biological variability from systematic error.
📬 Free: the IA topic-picker checklist + examiner tips
Get the Topic-Picker & Top-Band Checklist (PDF) plus short, examiner-written tips for each stage of your IA — straight to your inbox. No spam, unsubscribe any time.
✅ You're in! Grab your checklist now: download the PDF — tips will follow by email.
IA ideas for other subjects
Chemistry IA → Physics IA → Maths AA → Psychology IA → Geography IA → All 37 IA tools →