The internal assessment is an investigation of your own research question, worth 20% of your IB Biology grade at SL and HL. Here is how it is marked, criterion by criterion, and how to plan, analyse and write it up.
What the IA is
The IB calls it “an open-ended task in which the student gathers and analyses data in order to answer their own formulated research question.” It must involve quantitative data, backed up by qualitative observations where they help.
Weighting
20% of the grade, at SL and HL
Marks
24: four criteria, 6 marks each
Length
A written report of at most 3,000 words
Time
About 10 hours of class time is recommended
Marking
Marked by your teacher, then moderated by the IB (your mark can move up or down)
Approaches
Lab work, fieldwork, spreadsheet analysis and modelling, data from a database, or a simulation, alone or combined
What counts towards the 3,000 words: your text. Charts and diagrams, data tables, equations, formulas and calculations, citations and references, the bibliography and headers do not count. Start the report with the title, your IB candidate code (for example xyz123), the candidate codes of any group members and the number of words. You do not need a cover page or a contents page.
Two rules to know early. The same work cannot count as both your IA and your Extended Essay. And missing or improper referencing counts as academic malpractice, so record every source as you use it.
The four criteria
Each criterion is worth 6 marks, so each is a quarter of the IA. Your teacher reads the whole report and picks the band that fits best, then a whole mark within it. The bands climb through the command terms: work that only states sits in 1–2, work that outlines or describes in 3–4, and work that explains or justifies in 5–6.
Research design 6 marks
This criterion assesses the extent to which the student effectively communicates the methodology (purpose and practice) used to address the research question.
Marks
What your report shows
0
The report does not reach the 1–2 band.
1–2
The research question is stated with no context. Your methodological choices are only stated. The method is not detailed enough for someone else to repeat the investigation.
3–4
The research question is outlined within a broad context. You describe how you will collect relevant and sufficient data. Someone could repeat the method, with a few ambiguities or gaps.
5–6
The research question is described within a specific, appropriate context. You explain your methodological choices. Someone could repeat the investigation from your method.
What examiners look for
A research question that names the independent and dependent variables (or the two variables you are correlating) and the system you are studying
Background theory that is directly relevant to the question, not a general essay on the topic
Reasons for your measurement method, or for your choice of database or model and how you sampled it
A justified range, interval and number of repeats, and the precision of each measurement
Control variables, with how each one was controlled
Safety, ethical and environmental issues, where they apply
Common mistakes
A question with no specific context (no system, variables or theory). This caps the criterion at 3–4.
Listing control variables without saying how they were kept the same or why they matter
Too few repeats to see the variation in the data, or a range and interval that are never justified
A method too vague to repeat: missing volumes, concentrations, times or equipment
Data analysis 6 marks
This criterion assesses the extent to which the student's report provides evidence that the student has recorded, processed and presented the data in ways that are relevant to the research question.
Marks
What your report shows
0
The report does not reach the 1–2 band.
1–2
Recording and processing are neither clear nor precise. There is limited consideration of uncertainties. The processing has major omissions, inaccuracies or inconsistencies.
3–4
Recording and processing are either clear or precise, but not both. Uncertainties are considered, but with significant omissions. The processing has some significant omissions.
5–6
Recording and processing are both clear and precise. Uncertainties are considered appropriately. The processing is appropriate and accurate.
What examiners look for
Clear processing: a reader can follow how you got from the raw data to the result
Precise presentation: annotated tables and graphs, units, consistent decimal places and significant figures
Uncertainties recorded as ± ranges on raw data and carried into the processed data
Processing that answers your research question, such as means with standard deviation or error bars, or a statistical test
Common mistakes
No ± uncertainties on raw data, and no spread (SD, SE or error bars) in the processed data
Missing units, decimal places that change down a column, or unlabelled graph axes
Running a t-test or chi-squared test without knowing what it tests, or without saying what the result means
Putting key analysis in an appendix, where it may not be read as part of the report
Conclusion 6 marks
This criterion assesses the extent to which the student successfully answers their research question with regard to their analysis and the accepted scientific context.
Marks
What your report shows
0
The report does not reach the 1–2 band.
1–2
A conclusion is stated that is relevant to the research question but is not supported by the analysis. The comparison to the accepted scientific context is superficial.
3–4
A conclusion is described, but it is not fully consistent with the analysis. There is some relevant comparison to the accepted scientific context.
5–6
A conclusion is justified and fully consistent with the analysis, through relevant comparison to the accepted scientific context.
What examiners look for
A direct answer to your research question, quoting your processed results
An interpretation of the data that takes its uncertainties into account (this is what fully consistent means)
Comparison with published material, published values, course notes or textbooks, with traceable citations
Common mistakes
A conclusion based on raw observations, or one that never quotes a number
Claiming more than the data shows, for example ignoring overlapping error bars
No comparison with accepted science, or a source the reader cannot trace
Evaluation 6 marks
This criterion assesses the extent to which the student's report provides evidence of evaluation of the investigation methodology and has suggested improvements.
Marks
What your report shows
0
The report does not reach the 1–2 band.
1–2
Generic weaknesses or limitations of the method are stated. Realistic improvements are stated.
3–4
Specific weaknesses or limitations are described. Relevant, realistic improvements are described.
5–6
The relative impact of specific weaknesses or limitations is explained. Relevant, realistic improvements are explained.
What examiners look for
Weaknesses specific to your investigation: how well variables were controlled, the precision of your measurements, the variation in your data
Limitations: the range of your data, the confines of the system you studied, and the assumptions you made
Which weaknesses mattered most, and how each one affected your conclusion
Improvements that are realistic and tied to a weakness you identified
Common mistakes
Generic points that would fit almost any investigation, such as "human error" or "do more repeats"
A list of weaknesses with no sense of which had the biggest effect on the conclusion
Improvements that could not be done in a school lab, or that do not fix the weakness named
Band descriptors summarised from the IB Biology guide (first assessment 2025). The criteria changed for 2025, so ignore checklists written for the old IA.
Choosing a research question
Your research question shapes every criterion. A question with context names the independent and dependent variables (or the two variables you are correlating), describes the system, and is backed by directly relevant theory. Pick something you can measure well in about 10 hours, with enough data to see a pattern and its variation.
Too vague
How does temperature affect enzymes?
No enzyme, no system, no range and no measured variable. It could not be answered with one set of data.
Better
What is the effect of temperature (20, 30, 40, 50 and 60 °C) on the rate of starch breakdown by amylase, measured as the time taken for the solution to stop turning iodine blue-black?
It names the independent variable and its range, the dependent variable and how it is measured, and the system.
Too vague
Does light help plants grow?
"Help" and "grow" are not measurable as written, and it does not say which plant.
Better
What is the effect of light intensity, varied by the distance of a lamp from the plant, on the rate of oxygen production by pondweed, measured with an oxygen sensor?
Both variables are measurable, and the method of changing and measuring them is clear from the question.
Too vague
Is there a link between pollution and lichens?
Too broad: which pollutant, which lichens, and where would the data come from?
Better
Is there a correlation between the mean annual nitrogen dioxide concentration and the number of lichen species recorded at sites in a published survey database?
A database investigation: it names the two variables being correlated and the source of the data.
Before you commit, check that you can control the other variables, that the range and number of repeats are realistic, and that there are no safety, ethical or environmental problems you cannot deal with. Run a short pilot if you can: it shows whether the method works and whether your measurements are precise enough.
Planning, data, uncertainty and statistics
The guide’s skills sections, the Tools and the Inquiry process, are what the IA puts into practice. Inquiry 1 (exploring and designing) matches Research design, Inquiry 2 (collecting and processing data) matches Data analysis, and Inquiry 3 (concluding and evaluating) matches Conclusion and Evaluation.
Tool 1: Experimental techniques
Measure mass, volume, time, temperature and length to an appropriate precision, and make careful observations, including counts. Deal with safety, ethical and environmental issues. Techniques you may use include chromatography, colorimetry, serial dilutions, microscopy with an eyepiece graticule, temporary mounts, and random and systematic sampling.
Tool 2: Technology
Collect data with sensors, extract it from databases or generate it from models and simulations. Process it with spreadsheets, graphs, computer modelling or image analysis.
Tool 3: Mathematics
Averages and spread: mean, median and mode; range, standard deviation (SD), standard error (SE) and interquartile range.
Uncertainties: record them as ± ranges, show range, SD or SE as error bars, and give raw and processed uncertainties to a sensible precision.
t-test: tests whether the difference between the means of two sets of data is significant.
Chi-squared test: tests whether observed counts in categories differ significantly from the counts you expected.
Correlation: interpret the correlation coefficient (r), and use the coefficient of determination (R²) to judge how well a trend line fits.
Ecology: the Simpson reciprocal index for biodiversity and the Lincoln index for estimating population size.
Other calculations: percentage change and percentage difference, rates of change from graphs or tables, magnification and actual size from a scale bar.
Choose a test because it fits your data and your question, say what it tests, and interpret the result in words. A statistic with no interpretation earns little. Graphs should have labelled axes with units, error bars where you have them, and a line or curve of best fit where it makes sense.
The rules on group work and teacher feedback
Working in a group is optional, and only where your teacher allows it. A group can have no more than three students.
Each student formulates, investigates and answers their own research question. The IB says: “A student must not present the same set of raw data as another student.” So each of you uses a different independent variable, or the same independent variable with a different dependent variable, or different data from within a larger shared data set.
You write your report alone: “All authoring, including the description of the methodology, must be done individually.” A group report is not allowed. Sharing raw data or writing sections together is collusion.
Working alone, you can still ask classmates to help you collect data.
If you use a database your class built together, the IB treats it as a database investigation, so your method should explain how you filtered and sampled the data.
Teacher feedback: your teacher reads one draft and advises you on it, spoken or written, but cannot edit it. The next version you hand in is your final report, so make that draft as complete as you can.
Timeline checklist
Your school sets the deadlines. Work through these stages in order.
Read around topics that interest you and note the sources you use.
Write a research question with both variables and the system, and check it with your teacher.
Choose the range, interval and number of repeats, list the control variables and how you will control them, and do a risk assessment.
Run a pilot and adjust the method.
Collect your data, with units and uncertainties in every table, and note any problems as they happen.
Process the data: means, spread, graphs with error bars, and a statistical test where it fits.
Write the conclusion, comparing your results with published science and citing your sources.
Write the evaluation: specific weaknesses and limitations, their relative impact, and realistic improvements.
Hand in your one draft for feedback.
Act on the feedback, check the word count, add your candidate code and the title, and hand in the final report.
Frequently asked questions
How long should the IB Biology IA be?
The report has a maximum of 3,000 words. Charts, diagrams, data tables, equations, calculations, citations, references, the bibliography and headers do not count towards the limit. Put your title, your IB candidate code, the codes of any group members and the word count at the start.
Is the IA different at SL and HL?
No. The requirements are the same at SL and HL, and the IA is worth 20% of the grade at both levels. The same IA requirements apply to biology, chemistry and physics.
Can I do my IA with a partner?
Only if your teacher allows it, and in a group of no more than three students. Each of you needs your own research question and must not present the same raw data as anyone else. Each of you writes your own report, including the method.
How much help can my teacher give me?
Your teacher can read one draft and give you advice on it, spoken or written, but cannot edit it. The version you hand in after that feedback is your final report.
Does the IA have to be a lab experiment?
No. It can be hands-on lab work, fieldwork, spreadsheet analysis and modelling, data taken from a database, or a simulation, alone or combined. Whatever you choose, it must produce quantitative data.
Need help with your IA? Book a tutor
A tutor can help you sharpen your research question, plan your method and make sense of your statistics. Your report must still be your own work.
From the IB Biology guide (first assessment 2025). Always check your school’s deadlines and the latest guidance with your teacher. Clock it with SCI is not affiliated with the IB.
