The Internal Assessment is a significant, often underestimated component of the IB Diploma — typically worth 20-25% of the final grade in Sciences, Maths and Economics. Here's practical guidance on approaching it well.
How Much Does the IA Matter?
| Subject | Typical IA Weighting |
|---|---|
| Sciences (Biology, Chemistry, Physics) | 20% |
| Mathematics AA/AI | 20% |
| Economics | 20-25% |
Choosing a Good Topic
The most common mistake across all subjects is choosing a topic that's too broad or ambitious to investigate properly within the required scope. A good IA topic is:
- Specific — narrow enough to investigate deeply rather than superficially covering a broad area
- Genuinely investigable — realistic given the time, equipment and resources actually available to you
- Personally engaging — genuine interest sustains motivation through a lengthy independent project
- Course-relevant — allows meaningful application of specific syllabus content, not just general description
Subject-Specific Tips
Sciences
Strong Science IAs typically involve a clear research question, appropriate experimental design with identified variables, and thorough uncertainty/error analysis — this last part is where many students lose marks by treating it superficially.
Mathematics
The Maths Exploration should demonstrate genuine mathematical engagement — not just applying a formula, but exploring why it works, testing its limits, or extending it in some way. Personal engagement and reflection are explicitly assessed criteria.
Economics
The Economics IA requires analysing a real, current news article using appropriate economic theory and diagrams. Common pitfalls include choosing an article that doesn't allow for genuine economic analysis, or failing to evaluate the argument critically.
Timeline Tips
- Start topic selection early — rushed topic choices often lead to investigability problems discovered too late
- Build in time for a full draft and revision based on feedback before the final deadline
- Don't underestimate data collection/analysis time, particularly for science experiments requiring multiple trials