A strong IB Biology IA research question identifies a specific biological relationship that can be investigated using sufficient quantitative data. It should state the variables or correlation being studied, define the biological system, and be narrow enough to answer through a realistic, ethical methodology.
Under the current course, first assessed in 2025, the Biology IA is officially called the scientific investigation. According to the IB Biology subject brief, it is an open-ended investigation in which a student gathers and analyses data to answer their own research question. The report has a maximum of 3,000 words, contributes 20% of the final grade at both SL and HL, and is assessed using four criteria: research design, data analysis, conclusion, and evaluation.
What makes an IB Biology IA research question strong?
A strong question is focused, measurable, biologically relevant, and feasible. It normally identifies an independent variable and dependent variable, or two correlated variables for a database or field investigation, while briefly specifying the organism or biological system.
The current research design criterion considers the research question together with its context. This means that a polished question alone is not enough. Your surrounding explanation must establish the biological theory behind the investigation and justify the methodological choices used to answer it.
Use this general structure for a controlled experiment:
How does [independent variable, with unit or range] affect [measurable dependent variable, with unit] in [organism or biological system], measured using [appropriate technique or time frame]?
For example:
How does sucrose concentration from 0.00 to 1.00 mol dm⁻³ affect the percentage change in mass of potato (Solanum tuberosum) cylinders after 40 minutes of immersion?
This question establishes what will change, what will be measured, the organism involved, the range of treatment, and the duration. A reader can already anticipate the type of data, graph, controls, and biological explanation the investigation will require.
The essential components of the question
| Component | What it should communicate | Example |
|---|---|---|
| Independent variable | The factor deliberately changed | Sucrose concentration in mol dm⁻³ |
| Dependent variable | The quantitative response measured or calculated | Percentage change in mass |
| Biological system | The organism, tissue, enzyme, population, or process studied | Potato tissue |
| Scope | The range, treatment period, location, or dates | 0.00 to 1.00 mol dm⁻³ for 40 minutes |
| Measurement approach | How the response will be determined, where clarification is useful | Initial and final mass measured with a balance |
Units and ranges should be included when they make the question clearer, but the question must remain readable. If naming every concentration produces an unwieldy sentence, state the overall range in the question and list the exact treatment levels in the methodology.
Using a scientific name can improve precision when species identity affects the biology. However, neither a scientific name nor exactly five treatment levels is a universal rule stated in the official criterion. The more important requirement is that the system is clearly described and the methodology produces sufficient relevant data.
Vague versus precise research questions
Broad questions usually conceal decisions that should already have been made. Compare the following examples.
| Vague question | Main weakness | More precise version |
|---|---|---|
| How does light affect plants? | Neither light nor plant response is defined | How does blue-light intensity from 1,000 to 5,000 lux affect the mean increase in stem length of basil (Ocimum basilicum) seedlings over 14 days? |
| Does temperature affect catalase? | The response, enzyme source, range, and method are unclear | How does temperature from 10°C to 50°C affect catalase activity in potato extract, measured as oxygen volume produced per minute during hydrogen peroxide decomposition? |
| How does salt affect germination? | “Affect” could refer to germination percentage, speed, or growth | How does sodium chloride concentration from 0.00 to 0.20 mol dm⁻³ affect the germination percentage of radish (Raphanus sativus) seeds after 72 hours? |
| Is air pollution related to asthma? | Population, location, period, and measurements are absent | To what extent is annual mean PM2.5 concentration correlated with the annual rate of asthma-related hospital admissions across selected English regions from 2015 to 2024? |
Precision does not mean adding technical detail merely to make the question sound advanced. Every detail should define the investigation or prevent ambiguity. The RevisionDojo guide to refining an IA research question provides additional examples of narrowing a broad topic into an answerable question.
Build the question from a biological rationale
A research question should emerge from biology, not simply from available equipment. Begin with a mechanism or relationship that you can explain using established theory.
For an osmosis investigation, for example, the rationale is that differences in water potential cause net water movement across partially permeable cell membranes. This gives a reason to predict that changing external sucrose concentration will alter tissue mass. Your background section should explain that mechanism, define the relevant concepts, and support important claims with credible sources.
A useful planning sequence is:
- Choose a biological process, such as enzyme activity, photosynthesis, osmosis, germination, or population distribution.
- Identify one factor that could influence that process.
- Decide what quantitative response would represent the process validly.
- Explain the biological mechanism connecting the variables.
- Select a realistic range that could reveal a pattern without harming organisms or exceeding equipment limits.
- Pilot the method before finalising the wording.
The rationale usually belongs in the context and hypothesis rather than being packed into the research question itself. A concise hypothesis might predict that catalase activity will rise as temperature increases toward an optimum because molecular collisions become more frequent, before falling as enzyme structure is disrupted.
Students needing possible starting points can consult RevisionDojo's Biology IA ideas, but an idea should always be adapted to available materials, local conditions, and the student's own methodological decisions.
How the research question shapes the investigation
The research question is not an isolated sentence. It determines what evidence must be gathered and therefore influences every major section of the report.
Methodology and controls
Your independent variable determines treatment levels, while your dependent variable determines the instruments, units, measurement uncertainty, and processing method. The biological system reveals likely control variables, such as temperature, pH, specimen size, exposure time, substrate concentration, or developmental stage.
A question about temperature and enzyme activity, for example, requires controlled pH and enzyme concentration. A question about light intensity and photosynthesis requires careful control or monitoring of temperature because lamps can heat the experimental system.
Data analysis
The wording determines the appropriate data display and analysis. A continuous independent variable may produce a scatter graph and regression analysis, while comparisons between treatment groups may require means, measures of spread, error bars, and a suitable inferential test.
Do not choose a statistical test merely because it appears sophisticated. It must match the type of variables, distribution, sample structure, and assumptions of the test.
Conclusion and evaluation
The conclusion must answer the exact question using processed data, uncertainty, and statistical evidence where appropriate. The evaluation should then examine limitations that affect that answer, rather than listing generic problems such as “human error.”
The RevisionDojo sample Biology IA walkthrough illustrates how a question connects to variables, data collection, and interpretation. Students can also inspect different question styles in the Biology IA exemplar collection, although exemplars should be analysed rather than copied.
Experimental, field, and database questions
Not every valid Biology IA must be a laboratory experiment. The IB's sciences support resources discuss alternative approaches where access to school laboratory resources is limited.
| Investigation type | Typical question structure | Important design concern |
|---|---|---|
| Controlled experiment | How does X affect Y in system Z? | Controls, treatment range, repeats, and measurement validity |
| Field investigation | How does Y vary with X along or across a defined habitat? | Sampling method, spatial scale, weather, and confounding variables |
| Database investigation | To what extent is X correlated with Y in a defined population and period? | Database credibility, filtering, sample selection, missing values, and correlation versus causation |
| Simulation | How does changing parameter X affect simulated biological output Y? | Model assumptions, parameter validity, and biological interpretation |
For a correlational question, do not label one variable “independent” in a causal sense unless the design justifies causal inference. Use wording such as “To what extent is X correlated with Y?” and acknowledge plausible confounding variables.
A practical quality-control checklist
Before collecting final data, check that you can answer yes to each question:
- Is the relationship clearly biological rather than mainly chemical or psychological?
- Are the manipulated and responding variables, or the two correlated variables, unambiguous?
- Is the dependent variable quantitative and measured using a valid method?
- Is the organism, tissue, population, or system sufficiently defined?
- Can the method generate enough data to identify a meaningful pattern?
- Can important variables be controlled, measured, or discussed as confounders?
- Is the range biologically justified and practical?
- Can the investigation be completed safely, ethically, and within available time?
- Does the wording avoid assuming the result before evidence is collected?
- Can the expected relationship be explained through relevant biological theory?
A pilot study is particularly valuable. It can reveal that a concentration range is too narrow, a response is too small to measure reliably, or the chosen duration causes ceiling effects. Revise the research question when pilot evidence shows that the original design cannot answer it convincingly.
Common mistakes to avoid
One common mistake is treating complexity as quality. An investigation with several independent variables becomes difficult to control and interpret, while two dependent variables can consume space without adding meaningful insight. A focused study of one defensible relationship is usually stronger.
Other recurring problems include:
- Using “best,” “healthiest,” or “most effective” without defining a measurable criterion.
- Writing a yes-or-no question when a quantitative relationship could be investigated.
- Choosing treatment values before researching biologically relevant ranges.
- Naming a measurement that does not validly represent the biological process.
- Making causal claims from observational database data.
- Copying a familiar experiment without adapting or justifying the design.
- Ignoring safety, environmental effects, or the welfare of organisms.
The RevisionDojo Biology IA essentials guide explains the wider investigation requirements, while its eight Biology IA tips connect research design with analysis and evaluation.
Conclusion
A strong IB Biology IA research question defines a focused biological relationship, measurable variables, an identifiable system, and a realistic scope. Its quality depends not only on wording but also on whether relevant theory supports it and whether the methodology can produce sufficient, reliable data.
Draft several versions, test the method on a small scale, and revise the question before full data collection. RevisionDojo's IA guides and Jojo AI can help you examine clarity and identify missing design decisions, while your final scientific choices must remain your own. For exam preparation alongside the IA, use the IB Biology past paper video solutions to practise data interpretation and see the reasoning behind individual questions.
Sources and referenced URLs
- International Baccalaureate Biology subject brief, first assessment 2025
- International Baccalaureate: Biology in the Diploma Programme
- International Baccalaureate DP sciences support resources
- RevisionDojo: Refine your IA research question
- RevisionDojo: Biology IA ideas
- RevisionDojo: Sample Biology IA walkthrough
- RevisionDojo: Biology IA exemplars
- RevisionDojo: Biology IA essentials
- RevisionDojo: Eight Biology IA tips
- RevisionDojo: IB Biology past paper video solutions
