IB Physics IA Examples

The IB Physics Internal Assessment is a practical investigation worth 20% of your final grade. Physics IAs are particularly unforgiving on data quality: examiners expect quantitative analysis, proper uncertainty propagation, and graphs that are correctly processed. A student who designs a clever investigation but takes sloppy data will score lower than a student who runs a simpler experiment with rigorous measurement. This guide covers which IB Physics IA topics produce reliable high scores and what the marking criteria actually require.

Marking Criteria Overview

• Research design (6 marks): A focused research question in a genuine context — a non-standard variable, a context from the student's own life, or an original approach strengthens the design.
• Exploration (6 marks): Research question, background theory, identified variables (IV, DV, controlled), and a methodology detailed enough to be reproduced.
• Analysis (6 marks): Processed data with uncertainties, appropriate graphs (often linearised), and a conclusion with a comparison to expected values or theory.
• Evaluation (6 marks): Specific, directional assessment of limitations and improvements. Random vs systematic error distinction. This is where most marks are lost.
• Communication (4 marks): Clear structure, correct physics notation, appropriate length.

IB Physics IA Examples That Score Well

1. Simple harmonic motion — spring constant or pendulum period

Investigating how the period of a spring-mass system varies with mass (T = 2π√(m/k)) is a clean, quantitative Physics IA. The key to a high score is linearisation: plot T² vs m and fit a straight line, extracting k from the gradient. This demonstrates mathematical processing (Analysis criterion) beyond simply plotting T vs m. Adding error bars on both axes and a best-fit/worst-fit line analysis to determine uncertainty in k pushes the Analysis score to 5 or 6.

Personal context: investigate the spring constant of a specific object with physical meaning — the spring in a retractable pen, a bungee cord sample, a guitar string under tension. This transforms a textbook lab into an original investigation.

2. Optics — focal length of lenses using the lens equation

Measuring image and object distances for convex lenses and applying 1/f = 1/v + 1/u is a reliable method. A strong version linearises the equation (plot 1/v vs 1/u, extract f from the intercepts), compares the experimental focal length to the manufacturer's specification, and discusses how lens aberrations affect accuracy at small object distances. Personal engagement: use lenses from a real optical system — reading glasses, a camera lens, a magnifying glass from a specific application.

3. Projectile motion and drag

Investigating how launch angle or initial speed affects range — and then extending to quantify the effect of air resistance — is engaging and produces good data. Video analysis (using Tracker or equivalent software) allows frame-by-frame position measurement, making the velocity and acceleration calculations rigorous. A student who extracts a drag coefficient from the data and compares it to expected values for the projectile's shape earns strong Analysis and Evaluation marks.

4. Electromagnetic induction — Faraday's law

Dropping a magnet through a coil and measuring the induced EMF as a function of magnet speed, coil turns, or magnet strength directly tests Faraday's law (EMF = -dΦ/dt). This works well because it generates multiple measurable variables, is quantitatively predictable, and the deviations from ideal behaviour (flux leakage, finite coil resistance) provide rich Evaluation content. A data logger or oscilloscope makes the measurement precise; a smartphone with a magnetometer app can substitute in a resource-limited school.

5. Specific heat capacity of metals or liquids

Measuring specific heat capacity by electrical heating (E = mcΔT) is accessible, quantitative, and directly comparable to literature values. The investigation is most original when applied to a non-standard material: different cooking oils, metals from specific alloys, or composite materials. The systematic error from heat loss to the surroundings is significant and must be addressed in Evaluation — either by applying a cooling correction or by estimating the heat loss rate and showing its effect on the result.

Linearisation: The Most Important Analysis Skill

Physics IAs almost always involve a relationship between two variables that is not linear in its raw form. Examiners reward students who linearise their graphs because it demonstrates understanding of the underlying physics.

Common linearisations in IB Physics:

• T = 2π√(L/g) → plot T² vs L to get a straight line with gradient 4π²/g
• E = hf - φ → plot maximum kinetic energy vs frequency (photoelectric effect)
• I = I₀e^(-μx) → plot ln(I) vs x to get a straight line with gradient -μ
• v² = u² + 2as → plot v² vs s to get gradient 2a
• P = IV → if investigating resistance, plot V vs I to confirm linearity (Ohm's law)

Once linearised, use the gradient and intercept to extract physical constants, then compare to accepted values and calculate percentage error.

Uncertainty Analysis: What Examiners Actually Want

The single most common reason Physics IAs score Analysis = 3 or 4 instead of 5 or 6 is incomplete uncertainty handling. What examiners expect:

1. Record absolute uncertainty for every measuring instrument (ruler: ±0.5 mm, stopwatch: ±0.1 s, digital balance: ±0.01 g).
2. Calculate absolute uncertainty of derived quantities using propagation rules.
3. Plot error bars on graphs (both x and y if both have significant uncertainty).
4. Draw a best-fit line AND a worst-case line (max gradient, min gradient) to determine the uncertainty in any gradient you extract.
5. Express the final result as value ± uncertainty with appropriate significant figures.
6. Compare your percentage uncertainty to your percentage error from the accepted value — and explain the discrepancy if they differ significantly.

Evaluation: How to Write It Well

The Evaluation criterion rewards students who go beyond listing errors to actually analysing them. The structure that consistently earns 5–6 marks:

• Identify the limitation specifically: Not "human error" — name the exact source (parallax reading a ruler, air currents in the lab, temperature drift during a 30-minute experiment).
• State whether it is random or systematic: Random errors increase scatter; systematic errors shift all values in one direction.
• Quantify the effect where possible: "The temperature rose by 2°C during the experiment; using the temperature coefficient of resistance for copper, this introduces a systematic 0.8% error in resistance."
• Propose a concrete improvement: Not "be more careful" — identify a specific change (use a thermostatically controlled enclosure, replace the stopwatch with a light gate, use a digital vernier instead of a ruler) and explain why it would reduce that specific error.

Get Feedback Before Your Teacher Submits

Physics IA marks are often lower than students expect because the gap between "correct experiment" and "correct report" is larger than it appears. A well-run investigation with poorly presented uncertainty analysis or vague Evaluation loses 4–6 marks needlessly.

IBLens analyses your Physics IA against the official IB marking rubric and identifies exactly where marks are being lost on each criterion — before your teacher finalises the moderated submission.

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