RevisionDojoIB Math AI Internal Assessment: 12 Common Pitfalls and How to Avoid Them
Writing a strong IB Math AI Internal Assessment (IA) is about more than just solving math problems — it’s about demonstrating clear understanding, originality, and precision. Unfortunately, many students lose marks due to avoidable mistakes. In this guide, we break down the 12 most common pitfalls and give you practical tips to steer clear of them.
1️⃣ Excessive Writing Beyond the Page Limit
Writing too much can weaken your argument and reduce clarity.
✅ Solution: Be concise. Focus on relevant math, analysis, and reflection. Stick to the recommended length (typically 6-12 pages).
2️⃣ Failing to Cite Sources Properly
Not citing ideas, data, or formulas can lead to academic honesty issues.
✅ Solution: Use in-text citations and a bibliography. Acknowledge all external sources, including software, articles, and datasets.
3️⃣ Using Complex Math Without Understanding
Overcomplicating math can backfire if you can’t explain it.
✅ Solution: Only use techniques you fully understand and can justify. Clarity matters more than complexity.
4️⃣ Poor Labeling of Tables, Graphs, and Charts
Unlabeled visuals confuse the examiner and cost marks.
✅ Solution: Label axes, titles, units, and legends clearly on all visuals.
5️⃣ Insufficient Independent Research
Relying on textbook examples or copying ideas shows low engagement.
✅ Solution: Explore real-world data, original models, or unique scenarios.
6️⃣ No Explanation of Calculator or Software Use
Just presenting results without explaining how you got them loses clarity points.
✅ Solution: Describe how you used technology to solve problems or derive functions.
7️⃣ Misinterpreting Research Question or Command Terms
Confusing terms like calculate vs write down leads to incomplete work.
✅ Solution: Study IB command terms and make sure you fully understand your research question before starting.
8️⃣ Vague or Overly Broad Research Question
A weak question leads to unfocused analysis.
✅ Solution: Formulate a clear, specific, and manageable question that directs your investigation.
9️⃣ Copying Methodologies Without Understanding
Copy-pasting methods without comprehension results in weak analysis.
✅ Solution: Adapt methods to your context and explain them in your own words.
🔟 Choosing Overly Complex or Unworkable Topics
Ambitious but unmanageable topics make it hard to produce quality work.
✅ Solution: Choose a focused, realistic topic that allows for sufficient mathematical modeling and data.
11️⃣ Verbose or Repetitive Writing
Lengthy writing doesn’t mean better writing.
✅ Solution: Aim for precision. Each paragraph should add value to your investigation.
12️⃣ Lack of Personal Engagement
A generic IA without personal reflection or curiosity loses marks for engagement.
✅ Solution: Show your genuine interest — explain why you chose your topic and reflect on what you learned.
Summary of Common Pitfalls and Solutions
Here’s the common pitfalls and how to avoid them list in bullet point format for easy reference:
- Excessive writing: Be concise and stay within page limits.
- Missing citations: Cite all sources correctly.
- Complex math without understanding: Use math you can explain clearly.
- Poor labeling of visuals: Label charts, tables, and graphs accurately.
- Insufficient research: Go beyond textbooks and show originality.
- No explanation of tech use: Explain calculator or software steps clearly.
- Misinterpreting terms: Understand IB command terms and your research question fully.
- Vague research question: Formulate a focused, specific, and manageable question.
- Copying without understanding: Adapt and explain methods in your own words.
- Overly complex topic: Pick a focused, data-rich, and realistic topic.
- Verbose writing: Write clearly, precisely, and avoid unnecessary repetition.
- Lack of personal engagement: Show curiosity, initiative, and reflect on your process.
Final Tip
Avoiding these pitfalls is key to scoring highly in your IB Math AI IA. Plan carefully, stay focused, and make sure your work reflects both mathematical rigor and personal engagement.
👉 Want structured IA guidance, examples, and tools? Check out RevisionDojo’s Math AI IA resources — designed to help you avoid these pitfalls and excel.
