Biology Extended Essays are unique among IB EE subjects because they require primary research — you design and conduct your own experiment. This is both the greatest challenge and the greatest opportunity. A well-designed Biology EE with clean data and genuine analysis stands out immediately from essays that are purely based on secondary research.
Biology EE Research Questions: The Formula
Biology RQs follow a specific pattern: "What is the effect of [independent variable] on [dependent variable] in [organism/system]?" This structure forces you to design an experiment with a clear hypothesis and measurable outcome.
| Weak RQ | Strong RQ |
|---|---|
| "How does caffeine affect cells?" | "What is the effect of varying concentrations of caffeine (0, 50, 100, 200, 400 mg/L) on the rate of mitosis in Allium cepa root tip cells?" |
| "Does light affect plant growth?" | "To what extent does the wavelength of light (red vs. blue vs. white) affect the rate of photosynthesis in Spinacia oleracea as measured by oxygen production?" |
| "How do antibiotics work?" | "What is the effect of varying concentrations of amoxicillin on the zone of inhibition in Escherichia coli cultures?" |
Tip
The specificity is everything. "Allium cepa root tip cells" is specific. "Cells" is not. "Rate of mitosis" is measurable. "Cell health" is not. Make your independent variable, dependent variable, and organism all specific from the start.
Designing Your Biology EE Experiment
Independent Variable
The one thing you change. Use at least 5 concentrations or conditions for a meaningful range. Wider ranges with more data points give you stronger statistical results.
Dependent Variable
What you measure. Must be quantifiable and measurable with available equipment. "Rate of mitosis" (counted under microscope) is measurable. "Overall cell health" is not.
Controlled Variables
Everything else that could affect results: temperature, pH, light exposure, time, organism source. Document and control these rigorously — this is Criterion B (Application and Analysis).
Repetition
Conduct at least 5 trials per condition. Calculate means and standard deviations. Biology examiners expect statistical treatment of data.
Control Group
Always include a zero-concentration or untreated control. This is what your experimental results are compared against.
Statistical Analysis in Biology EEs
Biology EEs are expected to include statistical analysis of data. This is not optional — it directly affects your Criterion B score. Common statistical tests for Biology EEs:
- 1Mean and standard deviation (required for all quantitative data)
- 2Standard error and 95% confidence intervals (shows reliability of your mean)
- 3t-test (comparing two means — e.g., caffeine vs. no caffeine)
- 4ANOVA (comparing more than two groups — e.g., five concentrations)
- 5Correlation coefficient (if measuring a relationship between two continuous variables)
Literature Review for Biology EEs
Your literature review should introduce the biological mechanisms behind your experiment. If you're studying caffeine and mitosis, explain: what caffeine does biochemically, how mitosis works, and what previous research has found about caffeine's effect on cell division. This shows examiners you understand the underlying biology, not just your specific procedure.
Common Biology EE Organisms and Systems
| Organism/System | Good For Studying |
|---|---|
| Allium cepa (onion) root tips | Mitosis, chromosome behaviour, cell division inhibition |
| Spinach leaves (Spinacia oleracea) | Photosynthesis rate, chlorophyll effects |
| Yeast (Saccharomyces cerevisiae) | Fermentation, enzyme activity, substrate concentration |
| Daphnia (water fleas) | Heart rate effects, toxicity testing (ethical considerations) |
| Bacteria (E. coli or safe strains) | Antibiotic effectiveness, growth conditions |
| Germinating seeds | Enzyme activity, inhibitor effects, germination rates |
Note
Ethical constraints: Do not use vertebrates (fish, mice, birds) for experiments. Do not use human subjects. Allium cepa, yeast, and bacteria are commonly used precisely because they have no ethical restrictions.
Writing Your Conclusion
Your conclusion must: directly answer your RQ using your data, connect your findings to the biological theory you established in the literature review, explain any anomalies or unexpected results, and evaluate the limitations of your methodology.
Key Takeaways
- RQ formula: "What is the effect of [IV] on [DV] in [specific organism]?"
- Minimum 5 concentrations/conditions, 5 trials each, control group always included
- Statistical analysis is required — at minimum, mean and standard deviation
- Literature review establishes the biological mechanism BEFORE your experiment
- Conclusion must directly answer your RQ using your own data, not general biology knowledge