IB Physics EE Topics: 5 Examiner Checks to Pick a Feasible Question

High-scoring IB Physics Extended Essays share one trait: a narrow, physics-centred research question that produces either strong primary data or a rigorous methodological critique, matched to IB subject-specific guidance. The strongest essays borrow structure from examiner-marked exemplars, not from ambitious but unworkable ideas. Tiber Tutor’s examiner-built resources exist precisely to help students test that feasibility before committing months to a weak question.

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TL;DR:

• Focus your research question on a specific physics principle and ensure both variables are measurable within your available equipment.
• Prioritize experiments that generate clear primary data, especially in mechanics, waves, and circuits, rather than relying solely on literature sources.
• Conduct a feasibility check early, including calibration, pilot trials, and uncertainty methods, to avoid wasting time on unanswerable or impractical topics.
• Link theory closely to your data by deriving expected relationships beforehand and comparing them directly against your results with uncertainty analysis.
• Use examiner models and resources, like annotated exemplars and structured practice tests, to improve your critical evaluation and overall quality of your Physics extended essay.

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Table of Contents

• Ib physics ee topics organised by subfield
• How do you narrow a broad idea into a research question?
• What do top-scoring Physics EEs actually do differently?
• Should you run an experiment or write a literature review?
• A practical checklist for planning your investigation
• How do you write a research question that meets Physics EE requirements?
• What common mistakes weaken Physics EE topics?
• How do you connect theory to your experimental data?
• How should you manage and analyse your experimental data?
• Can Physics EE topics cross into other subjects?
• Where should you look for exemplars and official guidance?
• What examiners consistently reward, and what students underestimate
• Get examiner-built support for your Physics EE
• Sources
• FAQ

Ib physics ee topics organised by subfield

A good topic pool does not hand you a finished research question. It hands you a direction, then leaves the narrowing to you. Below are workable prompts across the major subfields, each flagged for whether it usually generates strong primary data, works better as simulation, or suits a literature-based approach. This is the stage where most students either set themselves up for a smooth six months or wander into a project that quietly falls apart in March.

Mechanics

1. How does the coefficient of restitution of a bouncing ball vary with drop height? (Experiment, easy data collection with slow-motion video.)
2. How does the launch angle affect the range of a spring-loaded projectile? (Experiment, good for testing kinematics against measured data.)
3. How does the damping coefficient of a pendulum change with fluid viscosity? (Experiment, needs careful timing and multiple fluids.)
4. How does mass distribution affect the period of a physical pendulum? (Experiment, straightforward apparatus, clean theory comparison.)
5. How does surface roughness affect the coefficient of kinetic friction on an inclined plane? (Experiment, but watch for inconsistent surface samples.)
6. How does string tension affect the speed of a transverse wave on a string, and does this match theoretical predictions? (Experiment, links mechanics and waves.)
7. What factors affect the terminal velocity of falling objects of different shapes? (Experiment, needs a tall drop height or high-speed camera.)
8. How does the angle of a ramp affect the rotational versus translational kinetic energy split for rolling objects? (Experiment, good for testing energy conservation.)

Thermodynamics

1. How does insulation thickness affect the cooling rate of a heated object, and does Newton’s law of cooling hold? (Experiment, simple data logging with temperature probes.)
2. How does the specific heat capacity of a mixture vary with composition ratio? (Experiment, calorimetry with careful heat loss correction.)
3. How efficient is a simple thermoelectric generator across a range of temperature differentials? (Experiment, needs a Peltier module and multimeter.)
4. How does ambient humidity affect the rate of evaporative cooling? (Experiment, good scope for a controlled comparison.)
5. What is the relationship between gas pressure and volume at constant temperature for a real gas, and how far does it deviate from ideal behaviour? (Experiment or literature, depending on equipment access.)

Waves and optics

1. How does slit width affect the diffraction pattern produced by a laser? (Experiment, needs a laser pointer, ruler, and dark room.)
2. How does the refractive index of a sugar solution change with concentration? (Experiment, clean linear relationship, good for uncertainty analysis.)
3. How does the thickness of a soap film affect the interference colours observed? (Experiment, tricky but visually striking data.)
4. How does polariser angle affect transmitted light intensity, and does this follow Malus’s law? (Experiment, cheap apparatus, strong theory fit.)
5. How does water depth affect the speed of ripple tank waves? (Experiment, good for testing wave speed formulas.)

Electricity and magnetism

1. How does the number of turns in a solenoid affect the induced EMF for a fixed magnet drop? (Experiment, needs a data logger for timing accuracy.)
2. How does temperature affect the resistance of a thermistor, and how well does it fit a known model? (Experiment, simple circuit, clear data trend.)
3. How does distance between capacitor plates affect capacitance, and does the parallel-plate formula hold at small separations? (Experiment, needs a sensitive capacitance meter.)
4. How does the strength of a magnetic field affect the force on a current-carrying wire? (Experiment, classic setup with a current balance.)

Modern physics and astrophysics

1. How does the photoelectric effect threshold frequency vary across different metal surfaces? (Experiment if equipment allows, otherwise literature-based.)
2. What do the light curves of eclipsing binary stars reveal about their relative sizes and masses? (Literature-based, using public survey data.)
3. How well do exoplanet transit models match published Kepler or TESS mission data for a chosen system? (Literature-based, strong for data analysis skills.)
4. How does radioactive decay data from a classroom source compare to theoretical half-life predictions? (Experiment, needs a Geiger counter and controlled shielding.)

Fluids and energy/power

1. How does pipe diameter affect flow rate for a fluid under constant pressure, and does it follow Poiseuille’s law? (Experiment, needs consistent tubing and a flow meter.)
2. How does blade angle affect the efficiency of a small wind turbine model? (Experiment, good scope for an engineering-flavoured EE.)
3. How does load resistance affect the power output of a small solar panel under constant illumination? (Experiment, useful for maximum power point discussions.)

Ideas built around waves, mechanics, and circuits tend to generate the cleanest primary data because the apparatus is simple and the theory is well established. Astrophysics and some modern physics topics work better as literature-based investigations, since replicating particle-physics or space-mission conditions in a school lab is rarely realistic.

How do you narrow a broad idea into a research question?

A workable Physics EE question does not arrive fully formed. It gets carved out through five checks, and skipping any of them is how students end up with a question they cannot actually answer in 4,000 words.

1. Ground it in a named physics principle. Your question should invoke a specific law, model, or relationship (Malus’s law, Poiseuille’s law, Newton’s law of cooling) rather than a vague “what affects X” framing.
2. Check syllabus overlap deliberately. IB subject-specific guidance recommends topics that use physics knowledge beyond the course, but not theory beyond what the student can genuinely explain.
3. Pick one independent and one dependent variable, both measurable. Multi-variable questions (“how do temperature and pressure and humidity affect…”) collapse under analysis. Isolate one relationship and control the rest.
4. Set a realistic parameter range. Decide the smallest and largest value of your independent variable before you start, and make sure the expected change in your dependent variable is large enough to see clearly against your measurement uncertainty.
5. Run a five-minute feasibility check. Can you get the equipment this week? Can you collect at least five trials per condition inside your school’s lab access? If not, narrow further or switch approach.

Red flags worth catching early: a question that needs university-level mathematics to interpret, a question requiring lab equipment your school does not stock, and a question so broad it could support three separate EEs. All three usually surface in the planning stage, before a single measurement is taken.

This narrowing step feeds directly into Criterion A (focus and method) and Criterion B (knowledge and understanding), since a well-scoped question makes it far easier to demonstrate command of the relevant physics without drowning in tangents.

Pro Tip: Write your research question as a single sentence with the independent and dependent variable named explicitly. If you cannot do that in one sentence, the question is not narrow enough yet.

What do top-scoring Physics EEs actually do differently?

Examiner-marked exemplars available through repositories such as Clastify reveal a consistent pattern: the essays that score highest are rarely the ones with the most exotic topic. They are the ones that execute a modest topic with total control.

• A tightly worded research question. The best essays state their question in the introduction without hedging, and every section afterwards visibly serves that question.
• Theory woven through the data, not bolted on before it. Strong essays introduce a physics model, derive the expected relationship, then repeatedly return to that model when discussing results.
• Explicit, quantified uncertainty treatment. Error bars appear on graphs, propagated uncertainties appear in tables, and the discussion addresses whether the uncertainty is small enough to support the conclusion.
• Honest evaluation of limitations. Rather than a token “sources of error” paragraph, strong essays explain specifically how each limitation could have shifted the result, and what a follow-up experiment would change.
• Evidence of pilot testing. Essays that mention a short pilot study to check variable ranges tend to show cleaner, better-scaled data in the final experiment, a pattern practical libguide advice also recommends.

Documenting equipment limitations and treating uncertainty explicitly is repeatedly flagged as a discriminating factor between mid-range and top-mark experiment-based essays. Annotated exemplars that pair the essay with examiner commentary are more useful than exemplars alone, because they show exactly which sentence or graph earned or lost marks against Criterion C (critical thinking) and Criterion D (presentation and evaluation).

The takeaway for planning: build your pilot trial into your timeline from day one, decide your uncertainty method before you collect a single data point, and write your limitations section as a genuine analysis, not an apology.

Should you run an experiment or write a literature review?

Neither approach outranks the other in IB Physics EE marking, but each carries different risks and different expectations for what “rigorous” looks like.

Experiment-based essays

• Generate original primary data, which examiners tend to reward when it is well controlled.
• Require calibrated equipment, a documented pilot trial, and a variable range chosen so the expected change is clearly visible above measurement noise.
• Demand repeatable trials, typically five or more per condition, with a transparent method for propagating uncertainty into the final result.
• Carry real risk if lab access is limited, since an experiment you cannot finish is worse than one you never started.

Literature-based essays

• Suit topics where school apparatus cannot realistically reach the required precision, such as astrophysics or particle physics.
• Must go beyond summarising sources. The essay needs to critically evaluate the methodology of each secondary source, compare their results, and explain discrepancies in methodological terms, not just report them.
• Depend entirely on the quality and traceability of sources; weak or unverifiable data undermines the whole essay.
• Reward strong synthesis and critique skills over practical lab dexterity.

Safety and ethics matter for experimental topics involving heat, electricity above a few volts, lasers, or radioactive sources. Check your school’s risk assessment procedure before finalising an experimental question, and build that approval time into your schedule rather than treating it as an afterthought.

A practical checklist for planning your investigation

A Physics EE rarely fails because the topic was bad. It usually fails because the timeline slipped, the equipment was not calibrated, or the uncertainty analysis was bolted on at the end. Work through this sequence instead:

1. Calibrate every instrument you plan to use before collecting real data, and record the calibration check in your notebook.
2. Run a short pilot trial to confirm your variable range produces a measurable, non-trivial change, and report that pilot data in your methodology.
3. Decide your data logging format upfront (spreadsheet columns, units, timestamps) so you are not reformatting data at 11pm before a deadline.
4. Calculate uncertainty as you go, not retroactively. Propagate instrument uncertainty through every calculation, and report it alongside every measured value.
5. Watch for parallax error, zero error, and reaction-time lag in manual measurements. These are the most common uncertainty sources examiners see repeated without correction.
6. Set a four-stage timeline: topic approval, pilot trial and safety sign-off, main data collection, and writing/analysis, each with its own deadline roughly a month apart.

Clear lab notebooks with timestamped raw data and reproducible analysis steps make it far easier to demonstrate rigour when an examiner checks your working. Tiber Tutor’s uncertainty calculations guide walks through error propagation methods step by step, which is worth working through before your first data collection session, not after.

Pro Tip: Keep a single running spreadsheet from day one of your pilot trial through to your final dataset. Retyping data between formats is where transcription errors quietly creep in.

How do you write a research question that meets Physics EE requirements?

A strong Physics EE research question does three things at once: it names a specific measurable relationship, it invokes a named physics principle, and it stays inside what you can actually test or research within the word limit. “How does temperature affect resistance?” is too vague. “How does temperature between 20°C and 80°C affect the resistance of a thermistor, and how well does this fit the manufacturer’s published resistance-temperature curve?” gives an examiner something concrete to follow from introduction to conclusion.

The IB’s own guidance stresses that the question should be narrow and not trivial, using physics knowledge that stretches the student without requiring theory beyond their grasp. In practice, that means avoiding two extremes. One extreme is a question so general it could fill a textbook chapter. The other is a question so simple that answering it demonstrates no real physics understanding, such as confirming a relationship every student already learned in class without adding a new variable, comparison, or context.

A useful test: write your question, then ask whether answering it requires you to derive or apply a specific formula, model, or law by name. If the answer is no, the question needs tightening. Naming the model up front, whether that is Poiseuille’s law, Malus’s law, or the thermistor’s resistance model, gives your entire essay a spine to build around, and it signals to the examiner from sentence one that you know exactly what you are testing.

What common mistakes weaken Physics EE topics?

The same handful of mistakes show up across weak Physics EEs, and every one of them is avoidable with earlier planning.

The most frequent is choosing a topic too broad to answer properly. “Investigating projectile motion” is not a research question, it is a chapter title. The fix is the narrowing process covered earlier: pick one variable pair, one physics model, one measurable range.

A close second is choosing a topic that needs equipment or precision beyond what a school lab can provide, then discovering that halfway through data collection. Running a genuine feasibility check, including a pilot trial, before committing to a full topic avoids this almost entirely.

Weak uncertainty treatment is another recurring issue. Essays that report a single measurement per condition, with no repeats and no propagated error, cannot support strong conclusions no matter how interesting the underlying idea is.

Overreaching on theory is a subtler trap. Some students borrow a formula from outside the syllabus without fully understanding it, then cannot explain it convincingly in their analysis. Examiners notice when a student is quoting a result rather than applying it.

Finally, vague or generic conclusions undercut otherwise solid essays. A conclusion should refer back to the specific research question, state the numerical result with its uncertainty, and compare that result honestly against the theoretical prediction, rather than closing with a general statement about the topic’s importance.

How do you connect theory to your experimental data?

The essays that read as genuinely rigorous are the ones where theory and data are in constant conversation, not separated into two halves of the report. Start by deriving the theoretical relationship you expect before you collect data, so you know what shape your graph should take. If you expect a linear relationship between force and extension, say so explicitly and explain why, citing the underlying physics law.

When you plot your results, overlay or compare them directly against that theoretical prediction rather than presenting the graph in isolation. State the percentage difference between your measured gradient and the theoretical value, and discuss whether that difference sits within your calculated uncertainty. If it does not, that is not a failure. It is an opportunity to discuss which limitation, whether friction, air resistance, or instrument lag, most plausibly explains the gap.

Avoid treating the “discussion” section as a place to restate results. Instead, use it to interrogate the fit between theory and data point by point: where the model held up well, where it broke down, and what that reveals about the physical system you tested. This is where Criterion C, critical thinking, is decided. An essay that only describes what happened scores lower than one that explains why the data behaved as it did in light of established theory.

How should you manage and analyse your experimental data?

Good data management starts before you take a single reading, not after. Set up your spreadsheet columns, units, and significant figures in advance, and decide your uncertainty method (instrument resolution, standard deviation across repeats, or a combination) before the first trial.

Run at least five repeats per condition where practical, and record every trial rather than only the “clean” ones. Discarding inconvenient data points without justification is one of the fastest ways to lose marks under Criterion D. If a reading looks anomalous, note it, investigate a plausible cause, and explain your decision to include or exclude it.

When analysing, propagate uncertainty through every calculated quantity, not just the raw measurements. A common shortcut error is reporting uncertainty on raw readings but ignoring how that uncertainty compounds through a calculation involving squares, ratios, or logarithms. Use a consistent method throughout, whether that is the maximum-minimum method or partial derivatives, and state which one you used.

Present your final result with its calculated uncertainty attached, and use that uncertainty range to judge whether your data actually supports or contradicts the theoretical prediction. A gradient of 9.7 ± 0.4 m/s² against a theoretical 9.81 m/s² is a strong, defensible result. The same gradient reported without an uncertainty range tells the examiner far less about how carefully you understood your own measurements.

Can Physics EE topics cross into other subjects?

Some of the most interesting Physics EEs sit at the boundary between physics and another IB science, provided the physics stays central to the research question. A biology-adjacent example might investigate how cantilever beam stiffness models apply to bird wing bending under load, keeping the analysis firmly rooted in mechanics rather than biology content. A chemistry-adjacent example could examine how the specific heat capacity of a solution changes with dissolved ion concentration, treating the chemistry as context for a physics measurement.

Environmental and engineering-flavoured topics work well too: measuring the efficiency of a small-scale solar panel under varying light conditions touches on renewable energy policy, but the actual research question, and the marking, stays entirely within physics concepts like power, efficiency, and circuit behaviour.

The key rule for any interdisciplinary Physics EE is that the research question, methodology, and analysis must be assessed as physics. If the essay drifts into biological explanation or environmental policy discussion without tying it back to a measurable physics relationship, it risks losing focus against Criterion A. Treat the other subject as the setting for your investigation, not as a second focus competing with the physics.

Where should you look for exemplars and official guidance?

Start with the primary authority: IB Answers and the official IB subject-specific guidance clarify assessment rules directly from the source, which beats relying on secondhand summaries. Reputable school libguides, including physics-specific pages built by teaching staff, are a solid second stop for practical planning advice like pilot trials and calibration steps.

For annotated exemplars, repositories such as Clastify’s Physics EE collection let you see full essays alongside their grades, though a useful exemplar is one you study for structure and technique, never one you paraphrase or copy from. Read exemplars to understand how a strong introduction frames a question, or how a strong discussion section handles uncertainty, then apply those patterns to your own topic in your own words.

Tiber Tutor supports this stage directly through its IB Physics topic tests, which help confirm your proposed topic sits solidly within syllabus knowledge, and its uncertainty calculations guide, built for exactly the kind of error propagation your EE will need to demonstrate.

What examiners consistently reward, and what students underestimate

The most common reason a Physics EE underperforms is not a weak topic. It is a strong topic executed with sloppy uncertainty treatment and a thin discussion of limitations. Students consistently underestimate how much marks hinge on Criterion C and D, the sections covering critical thinking and evaluation, rather than on how ambitious the subject sounds.

The single change that raises scores most reliably is treating the pilot trial and uncertainty method as part of the topic selection process, not an afterthought bolted on after data collection. Examiner-designed practice questions and structured performance analytics, like those built into Tiber Tutor by practising IB examiners, help students spot exactly where their physics reasoning is thin before that weakness ends up buried inside a 4,000-word essay.

— Oliver

Get examiner-built support for your Physics EE

Choosing a strong topic is only the first hurdle. Turning it into 4,000 words that survive Criterion C and D scrutiny takes a solid grip on the underlying physics, and that is exactly where Tiber Tutor earns its place: it is the only IB STEM platform built by practising IB examiners, with topic tests, mock exams, and progress analytics interlinked tightly enough that a weak spot in your syllabus knowledge shows up before it derails your EE analysis.

Work through Tiber Tutor’s IB Physics topic tests to confirm your EE question sits within solid syllabus knowledge, or check the complete IB Physics syllabus guide before finalising your research question. Pair that with the uncertainty calculations walkthrough to get your error propagation right from the first pilot trial, and lean on the IB Physics cram sheets when you need a fast formula check mid-analysis. Every resource tracks into the same personalised analytics dashboard, so you can see exactly which syllabus areas need work before your EE deadline arrives. Head to Tiber Tutor for students to start a free trial and see the full platform for yourself.

Sources

A literature-based Physics EE lives or dies on the quality and traceability of its sources. Peer-reviewed journal articles, official mission data releases (such as published exoplanet transit datasets), and textbooks with clear derivations are far stronger foundations than general science news articles, which often simplify or misstate the underlying physics.

When selecting sources, prioritise ones that publish their raw data or methodology, since your essay needs to critically evaluate that methodology rather than just cite the conclusion. A source that only states a result without explaining how it was obtained gives you nothing to critique, and critique is where Criterion C marks are won.

Cross-check figures across at least two independent sources where possible. If two papers report different values for the same quantity, that discrepancy is not a problem to hide. It is material for analysis: discuss what methodological differences might explain the gap.

Keep a running bibliography with access dates for any online source, since data repositories are sometimes updated or revised. Avoid relying on a single source for your entire argument, and be wary of tertiary sources like general encyclopaedias, which rarely provide the methodological detail a literature-based EE needs to meet examiner expectations.

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FAQ

What makes a good IB Physics EE topic?

A good topic is narrow, built around a named physics principle, and feasible to test with equipment your school actually has, matching the focus IB subject-specific guidance expects.

Should I choose an experimental or literature-based Physics EE?

Choose experimental if you have reliable lab access and want to generate primary data with controlled variables; choose literature-based if your topic (such as astrophysics) cannot realistically be tested at school scale.

How many words should an IB Physics EE be?

The IB Physics extended essay follows the standard EE word limit of 4,000 words across all subjects, covering introduction, methodology, results, and discussion.

Where can I find examiner-marked Physics EE exemplars?

Repositories such as Clastify publish annotated past essays, and reputable school libguides often link additional graded examples alongside examiner commentary.

How can Tiber Tutor help with my Physics EE?

Tiber Tutor’s topic tests and uncertainty calculations guide, built by practising IB examiners, help confirm your syllabus knowledge and error propagation method before you commit to a full research question.

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