A step-by-step writing frame for the IBDP Physics Internal Assessment. Each section pairs a place to write with the rubric, worked examples, and the traps that cost students marks — built around the governing equation, linearised graphs, and uncertainty propagation.
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A strong IB Physics Internal Assessment starts with a focused research question naming the independent and dependent variables, the range and the units, and the governing equation that predicts the relationship between them — for a simple pendulum, T = 2π√(L/g). Controlled variables are tied to the model's assumptions (the small-angle approximation, negligible air resistance), and materials and equipment are listed with their measurement uncertainties, applying the read-once versus read-twice rule for any length found as a difference of two readings. A reproducible method then yields data you propagate (absolute, percentage, and the rule for powers), plot as a linearised graph with error bars and max/min gradients so the gradient gives a physical quantity, and conclude by comparing that value with an accepted constant such as g within experimental uncertainty. Free to start; exports DOCX/PDF.
The IA is assessed against four equally weighted criteria worth 24 marks in total. Research design (6) rewards a focused question, justified variables and a reproducible method. Data analysis (6) rewards precise recording and processing with measurement uncertainty propagated throughout. Conclusion (6) rewards a quantified answer justified against an accepted value. Evaluation (6) rewards specific random and systematic weaknesses with targeted improvements. Personal engagement is no longer separately assessed.
The best Physics IAs linearise the governing equation into the form y = mx + c — squaring T = 2π√(L/g) gives T² = (4π²/g)L, so a graph of T² against L is a straight line through the origin whose gradient is 4π²/g. Error bars come from propagated uncertainties (add absolutes when subtracting, add percentages when multiplying, and multiply the percentage by n for a power n). Max and min gradients through the error bars give m ± Δm, and the gradient yields g.
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A good question is focused and manipulable: it names the independent variable with its range and units, the dependent variable and exactly how it is measured, and rests on a physical law you can write as an equation. Choosing a relationship that linearises to a straight-line graph — so the gradient yields a physical quantity such as g — is what lifts a question into the top band.
Rearrange the governing equation into the form y = mx + c. For a pendulum, T = 2π√(L/g) squares to T² = (4π²/g)L, so plotting T² against L gives a straight line of gradient 4π²/g through the origin. You then read a physical constant straight off the gradient, and a zero intercept becomes a built-in check on systematic error.
Add absolute uncertainties when adding or subtracting, add percentage uncertainties when multiplying or dividing, and multiply the percentage uncertainty by n when raising to the power n — so squaring a period doubles its percentage uncertainty. Build error bars from the propagated absolute uncertainties, then take max and min gradients through them to quote the gradient as m ± Δm where Δm = (m_max − m_min) / 2.
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