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The Evaluation section of your IB Biology IA showcases how effectively you can analyze and reflect on your investigation. In this part, you should assess the reliability of your findings, identify experimental strengths, pinpoint weaknesses, and suggest realistic improvements to the experiment. This post highlights some essential elements to consider when crafting an evaluation for your IB Biology IA.
IB Biology IA Evaluation
Highlight the strengths
A strengths section in the evaluation allows you to demonstrate aspects of the investigation that worked well. This may include well-controlled environmental conditions, reliable measurement tools, or an appropriate sample size. For example, an IA about enzymatic degradation could say, “Maintaining all test samples at a constant 25°C ensured that temperature did not influence enzyme activity, therefore increasing the reliability of the results.” Highlighting the strengths of your investigation shows awareness of what gave your results credibility and why your experimental method was scientifically sound. For a good example of how to highlight strengths, see this IA.
Explain the weaknesses and suggest improvements
Your evaluation should also address experimental limitations that reduced reliability or accuracy, and offer improvements to address them. You should avoid using vague statements like “human error affected the results” and should instead identify specific procedural or equipment-related issues. For example, an IA discussing how light intensity affects leaf transpiration could say, “A key weakness was variation in leaf thickness, which affected transpiration rates; using leaf discs of standardized mass would reduce this inconsistency.” Each weakness must identify a targeted improvement that would increase the precision or accuracy if the experiment were to be repeated in future. A good example can be seen here and here.
Discuss all types of errors
The discussion about experimental limitations should reflect random, systematic, and human errors wherever possible. You should explain how each type of error influenced your results. Random errors might arise from natural biological variability, while systematic errors may stem from instrument calibration issues or biased sample selection. For example, the evaluation for an IA about how pH affects bacterial growth could say, “A systematic error occurred because the pH probe had not been calibrated recently, consistently reading 0.1 units lower than actual values.” A thorough error discussion shows understanding of where uncertainty entered your experiment and how it affected your final results. A good example of when a student discussed various types of errors can be found here.
Provide some extensions to the experiment
Provide some extensions that demonstrate higher-level thinking by proposing broader applications related to your IA topic. These should build on your findings and explore related variables or improved methodologies. For example, an IA about exploring the effect of various alcohols on bacterial growth inhibition could say, “An extension could be to repeat the investigation with genetically distinct bacterial strains to determine whether the response pattern is conserved across populations.” Including thoughtful extensions shows that you understand the larger scientific context and can provide relevant ideas on how the research could be further explored. A good example of extensions can be found here.
We hope this post has helped you learn more about how to write an IB Biology IA evaluation. For more useful materials associated with the IB, check out the wide variety of IA, EE and TOK exemplars available at Clastify and other guides available on our blog.
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