- What Makes a Good Biology IA Topic?
- Biology IA Requirements (Guide First Assessed in 2025)
- Enzyme IA Ideas (C1.1 Enzymes and Metabolism)
- Respiration and Photosynthesis IA Ideas (C1.2, C1.3)
- Water Potential, Transport and Plant IA Ideas (D2.3, B3.1, B3.2)
- Human Physiology IA Ideas
- Ecology and Fieldwork IA Ideas (C4.1, A4.2, B4.1)
- Database and Simulation IA Ideas
- Food Science and Microbiology IA Ideas
- From Topic to Research Question: An Example
- Research Design: Methodology That Scores Well
- How the Four Biology IA Criteria Are Marked
- Common Biology IA Mistakes to Avoid
Quick Answer
Strong IB Biology IA topics have one independent variable you can change or select, a dependent variable you can measure as numbers, and enough data for statistics. Enzymes, photosynthesis, water potential, respiration, ecology fieldwork and database studies all work well. The IA is a scientific investigation worth 20% at SL and HL, with a 3,000-word limit and four criteria worth 6 marks each.
What You'll Learn
- The Biology IA is a scientific investigation worth 20% at SL and HL, with a 3,000-word maximum and four criteria worth 6 marks each
- The criteria are research design, data analysis, conclusion and evaluation; personal engagement, exploration and communication belong to the old guide
- Your research question must be your own, and you must not present the same raw data as another student
- Lab work, fieldwork, databases, spreadsheet models and simulations are all allowed if they produce quantitative data
- Choose a topic that gives enough data for statistics such as standard deviation, error bars and a t-test
What Makes a Good Biology IA Topic?
A good topic gives you a clear relationship to test: an independent variable you can change or select, a dependent variable you can measure as numbers, and other variables you can realistically control. The guide requires the investigation to collect and analyse quantitative data, supported by qualitative observations where appropriate, and to have enough extent and depth for every criterion to be addressed. It allocates about 10 hours of class time to the whole IA, so choose a method you can run and repeat quickly with equipment your school has.
Pro Tip
Start from the guide's skills list. It includes colorimetry, chromatography, serial dilutions, microscopy with an eyepiece graticule, sampling techniques and sensors, so a topic built on one of these techniques is usually feasible in a school lab.
Biology IA Requirements (Guide First Assessed in 2025)
Biology, chemistry and physics share the same IA model in the guides first assessed in May 2025, which apply to everyone sitting exams in November 2026, May 2027 and May 2028, including DP1 students who started in August 2026. The IA is one task, the scientific investigation: an open-ended investigation in which you gather and analyse data to answer your own research question.
- Weighting: 20% of the final grade at both SL and HL, with the same criteria at both levels
- Length: a written report of no more than 3,000 words; charts, diagrams, data tables, equations, calculations, citations, the bibliography and headers do not count
- Time: the guide recommends about 10 hours of teaching time for the IA
- Marking: research design, data analysis, conclusion and evaluation, each out of 6, for a total of 24; marked by your teacher and moderated by the IB
- Approaches: hands-on lab work, fieldwork, spreadsheet analysis and modelling, data from a database, or a simulation, alone or combined
- Group work: optional, in groups of no more than three, but each student needs their own research question and writes their own report
- Report details: title, IB candidate code (and group members' codes if relevant) and word count at the start; no cover or contents page is needed
Watch Out
If a website or older textbook mentions personal engagement, exploration, analysis, evaluation and communication criteria, a 6-12 page limit or the group 4 project, it describes the previous Biology guide. The group 4 project has been replaced by the collaborative sciences project, which is separate from the IA.
Enzyme IA Ideas (C1.1 Enzymes and Metabolism)
Enzyme experiments are popular because they are reliable, quick to repeat and tied directly to the syllabus content on temperature, pH and substrate concentration. That popularity is also the risk. A textbook catalase experiment needs a specific system, a wide range and a precise method to reach the top band.
- Temperature and catalase activity in yeast or potato (SL and HL): measure oxygen volume with a gas syringe, or the time for a filter-paper disc to rise, at 6-8 temperatures and locate the optimum. Stronger if you model the curve or compare two tissues.
- pH and amylase activity (SL and HL): follow starch breakdown with iodine using a colorimeter rather than judging colour by eye, which gives continuous absorbance data at each pH.
- Substrate concentration and reaction rate (SL and HL): vary hydrogen peroxide concentration by serial dilution, measure initial rates, and model how the rate levels off as active sites become saturated.
- Enzyme concentration and reaction rate (SL and HL): dilute amylase or catalase in steps and test whether the initial rate rises in proportion, explaining any departure from a straight line.
- Copper ions and enzyme activity (SL and HL): measure how copper sulfate concentration reduces catalase or amylase activity. HL students can compare the pattern with non-competitive inhibition, which is additional higher level content.
- Pectinase and juice yield (SL and HL): vary pectinase concentration or temperature and measure the volume of juice released from apple pulp in a fixed time.
- Temperature and protease activity (SL and HL): measure how quickly a protease such as trypsin clears a milk suspension at different temperatures, using a colorimeter. Follow your school's guidance on handling enzymes.
Respiration and Photosynthesis IA Ideas (C1.2, C1.3)
These topics give continuous data with sensors or simple gas measurements. The guide lists variables affecting the rate of cell respiration and techniques for varying carbon dioxide, light intensity and temperature in photosynthesis experiments, so the syllabus link is direct.
- Glucose concentration and yeast respiration (SL and HL): measure carbon dioxide released, by gas volume or mass loss, at 6-8 glucose concentrations. Comparing sugar types gives categorical data, so prefer a continuous variable.
- Temperature and respiration in germinating seeds (SL and HL): measure oxygen uptake with a simple respirometer, or carbon dioxide with a sensor, at a range of temperatures.
- Light intensity and photosynthesis in pondweed (SL and HL): collect the volume of oxygen produced at measured light intensities, using a light meter rather than distance from the lamp alone.
- Carbon dioxide and leaf disc flotation (SL and HL): vary sodium hydrogen carbonate concentration and time how long leaf discs take to float. Cheap, quick and easy to repeat many times.
- Wavelength and photosynthesis (SL and HL): use coloured filters and compare the rate with the absorption spectrum of chlorophyll. Measure the light reaching the leaf, because filters also reduce intensity.
- Pigments in sun and shade leaves (SL and HL): separate pigments by paper or thin layer chromatography, calculate Rf values, and compare chlorophyll concentration in extracts with a colorimeter.
Water Potential, Transport and Plant IA Ideas (D2.3, B3.1, B3.2)
Plant topics are cheap and easy to control, but growth experiments need weeks. Choose measurements that change within hours unless you can plan well ahead.
- Water potential of potato or sweet potato tissue (SL and HL): measure percentage mass change in 6-8 sucrose or salt concentrations and interpolate the concentration that causes no change. A clean design with clear processing.
- Membrane damage in beetroot (SL and HL): measure pigment leakage with a colorimeter after exposing discs to different temperatures or ethanol concentrations.
- Plasmolysis in onion or red cabbage cells (SL and HL): count the percentage of plasmolysed cells under the microscope at different salt concentrations.
- Wind speed and transpiration (SL and HL): use a potometer and a fan at measured air speeds, controlling light and temperature carefully.
- Stomatal density in sun and shade leaves (SL and HL): make nail-varnish leaf casts, count stomata in a known field of view and compare with a t-test. The guide names stomatal density as an application of skills.
- Salinity and seed germination (SL and HL): measure germination percentage or root length of cress or mung beans at different salt concentrations. Needs one to two weeks, so start early.
- Rooting hormone and root growth (SL and HL): vary the concentration of a rooting powder or gel on stem cuttings and measure root number or length. Needs two to three weeks and many cuttings.
Human Physiology IA Ideas
Human topics are engaging, but people vary a lot, so you need more participants or repeats. Follow the IB's ethical guidance: participants give informed consent, take part voluntarily and are not put at risk. Avoid anything that involves swallowing substances, discomfort or medical data, and agree the plan with your teacher before you start.
- Exercise intensity and heart rate recovery (SL and HL): measure how pulse rate recovers after step-ups at different stepping rates. Links to the measurement of pulse rates in B3.2.
- Lung volume and height (SL and HL): measure vital capacity with a spirometer and test the correlation with height or regular exercise. Links to the measurement of lung volumes in B3.1.
- Distraction and reaction time (SL and HL): measure reaction time with a ruler-drop or computer test at different background noise levels.
- Muscle fatigue (SL and HL): record grip strength with a dynamometer over repeated contractions and compare different rest intervals between sets.
Ecology and Fieldwork IA Ideas (C4.1, A4.2, B4.1)
In fieldwork you select variables rather than manipulate them, which the guide allows. Plan random or systematic sampling, collect enough samples for statistics, and use the guide's own tools such as quadrats, the Simpson reciprocal index and the Lincoln index.
- Lichen or moss cover and distance from a road (SL and HL): use quadrats along a transect and test the correlation with Spearman's rank, explaining why lichens can indicate air quality.
- Plant diversity in mown and unmown grass (SL and HL): calculate the Simpson reciprocal index from random quadrats in each area and compare them.
- Trampling and footpath plants (SL and HL): measure plant height and species richness at set distances from the edge of a path and test the trend.
- Leaf size in sun and shade (SL and HL): measure leaf area from scaled photographs on the sunny and shaded sides of the same trees and compare with a t-test.
- Woodlouse population estimates (SL and HL): use capture, mark and release with the Lincoln index in two habitats, marking animals harmlessly and returning them where you found them.
- Leaf litter invertebrates and soil moisture (SL and HL): extract invertebrates from litter samples of measured moisture with a Tullgren funnel and test the relationship.
- Rocky shore zonation (SL and HL): if you have access to a coast, run a belt transect from low to high tide and relate the abundance of limpets or seaweeds to height on the shore.
Database and Simulation IA Ideas
A database investigation is a full IA option. Your research design marks then depend on how you select, filter and sample the data, so explain those choices as carefully as you would a lab method.
- Genome size and complexity (SL and HL): extract genome sizes for different taxonomic groups from a public database and compare them with gene number or organism type. The guide uses this as an application of skills in A3.1.
- Is spring arriving earlier? (SL and HL): use long-term first-flowering or leafing dates from a national phenology or citizen-science database and test the trend against spring temperatures.
- Body mass and metabolic rate in mammals (SL and HL): take a published data set, plot it on logarithmic axes and find the scaling relationship.
- Shifting species ranges (SL and HL): use records from the Global Biodiversity Information Facility to test whether a species' range has moved north or uphill over decades. Plan how you will remove duplicate or unreliable records.
- A natural selection simulation (SL and HL): vary one parameter, such as selection pressure, in an online simulation and measure the change in allele frequency over generations. Justify every setting, because simulated data can look too clean.
Food Science and Microbiology IA Ideas
These ideas are popular but need extra care. Microbiology must use safe, non-pathogenic organisms, aseptic technique and sealed plates, and your teacher must approve the method.
- Vitamin C loss on heating (SL and HL): measure the vitamin C content of fruit juice by DCPIP titration after heating at different temperatures or for different times.
- Garlic or honey as an antimicrobial (SL and HL): measure zones of inhibition at different extract concentrations on plates of a safe bacterium, only with teacher approval and proper aseptic technique.
- Yeast population growth (SL and HL): count cells with a haemocytometer over time at different sugar concentrations and fit a growth curve. Links to populations in C4.1.
- Temperature and yoghurt fermentation (SL and HL): track the fall in pH with a probe as milk ferments at different temperatures.
From Topic to Research Question: An Example
The guide says a research question with context refers to the independent and dependent variables, or two correlated variables, describes the system being studied and includes directly relevant background theory. Here is an illustrative example of narrowing a topic down.
- 1Topic: enzymes and temperature
- 2Too broad: how does temperature affect enzymes?
- 3Better: how does temperature affect the activity of catalase?
- 4Focused: how does temperature (20, 25, 30, 35, 40, 45 and 50 °C) affect the initial rate of oxygen production by catalase in a yeast suspension, measured with a gas syringe?
- 5Context: explain the enzyme and its substrate, how temperature affects collisions and denaturation, and what you predict
Pro Tip
Revisit the research question after your pilot. Once you know the range that works, make sure the final question matches exactly what you measured.
Research Design: Methodology That Scores Well
The research design criterion rewards explaining your methodological considerations and describing a method someone else could reproduce. The guide lists these considerations: how you measure the variables, the range, interval and number of repeats, how you control other variables, and any safety, ethical or environmental issues.
- 1Justify the range and interval of your independent variable; five or more values is common practice and shows a trend clearly
- 2Plan enough repeats to calculate a mean and standard deviation for each value
- 3Explain how each controlled variable is kept constant and why it matters, rather than only listing it
- 4Give exact apparatus, volumes, concentrations and timings so the method could be repeated
- 5Run a pilot and say what it changed in your method
- 6Address the safety, ethical and environmental issues specific to your investigation
How the Four Biology IA Criteria Are Marked
Each criterion is out of 6 and worth 25% of the IA mark. These points paraphrase what the guide describes for the top band of 5-6 marks.
- Research design: the research question is described in a specific and appropriate context, methodological considerations are explained, and the method could be reproduced
- Data analysis: recording and processing are clear and precise, uncertainties are appropriately considered, and the processing is appropriate and accurate
- Conclusion: a conclusion relevant to the research question is justified, fully consistent with your analysis, and compared with the accepted scientific context
- Evaluation: you explain the relative impact of specific methodological weaknesses or limitations, and explain realistic improvements that address them
Pro Tip
In biology, uncertainty includes variability between repeats as well as instrument precision. The guide's maths skills include standard deviation, standard error, error bars, R squared for trend lines, and the t-test and chi-squared test, so use those that fit your design.
Common Biology IA Mistakes to Avoid
These mistakes cost students marks every year, and most of them are decided before any data is collected. If variables and controls are where you feel unsure, an IB Biology tutor can work through them with you on other investigations; feedback on your own design comes from your teacher.
- Choosing a topic without checking equipment, time and approval at your school
- Skipping a pilot, then finding the method does not work when it is too late to change
- Too few values or repeats to show a trend or support a statistical test
- Using a categorical independent variable when a continuous one would give stronger analysis
- Ignoring anomalies instead of identifying and explaining them
- A conclusion that restates the trend without comparing it with published scientific context
- An evaluation of generic errors, such as human error, instead of specific weaknesses and their impact
- Going over 3,000 words; work beyond the limit is not what the criteria reward
Watch Out
Never fabricate or adjust data. Examiners are experienced at spotting results that are too perfect, and academic misconduct can cost you your grade.