In IB Maths AI, modelling questions often feel uncomfortable because they move away from exact answers and into judgement. Many students respond by focusing even harder on formulas, believing that correct mathematics will carry them through. In reality, IB cares far more about the assumptions behind the model than the formulas used to build it.
A formula is only as good as the assumptions that support it. Modelling always involves simplifying reality. Students choose variables, ignore certain factors, and assume relationships behave in specific ways. These decisions shape the model far more than the algebra that follows. IB wants students to show awareness of this process.
One reason assumptions matter so much is that they define the scope of validity. A model may work well under certain conditions and fail completely under others. Students who apply formulas without stating or questioning assumptions often draw conclusions that sound confident but are unjustified. IB penalises this because it shows a lack of critical thinking.
Another issue is that many formulas are reused across different contexts. The same regression equation, probability model, or normal approximation can be applied to very different situations. What changes is not the maths, but whether the assumptions still make sense. IB tests whether students can judge this suitability.
Students often avoid discussing assumptions because they feel vague or subjective. In IB Maths AI, they are neither. Assumptions can be clearly identified and explained: independence, constant rates, linearity, normality, or representativeness. Naming and evaluating these earns valuable interpretation marks.
IB also uses modelling questions to test self-critique. Strong answers acknowledge weaknesses, such as ignored variables or unrealistic simplifications. Students sometimes worry this undermines their work. In fact, it strengthens it. IB rewards students who recognise that no model is perfect.
Another reason assumptions outweigh formulas is realism. In real applications, analysts rarely trust outputs without questioning inputs. IB mirrors this by prioritising reasoning over execution. A simple model with well-justified assumptions often scores higher than a complex model applied blindly.
Once students shift focus from “did I use the right formula?” to “are my assumptions reasonable?”, modelling questions become far clearer. The maths becomes a tool, not the goal.
In IB Maths AI, thinking about the model matters more than building it.
Frequently Asked Questions
Should I always state assumptions explicitly?
Yes, especially in modelling and interpretation questions. It shows control and awareness.
Can I lose marks for unrealistic assumptions?
Yes, particularly if you don’t acknowledge their limitations.
Are formulas still important?
Yes, but only when they are supported by reasonable assumptions.
RevisionDojo Call to Action
Modelling marks come from judgement, not just equations. RevisionDojo is the best platform for IB Maths AI because it trains students to identify assumptions, critique models, and write examiner-ready evaluations. If modelling questions feel vague or risky, RevisionDojo helps you turn uncertainty into marks.
