IB Physics SL Extended Essay Example

The research question is clearly identifiable and aligned to a real physics investigation. The student’s focus on launch angle, air resistance, and temperature gives the essay a coherent practical purpose, which helps the reader immediately understand the topic and its intended direction.

The question is still too imprecise: it does not state the temperature range, launch speed, launch height, or what “most optimum” means operationally. The student should rewrite it so the variables and success criterion are fully defined from the start.

The aim is relevant, but it would be stronger if it named the exact temperature interval and the fixed launch conditions. That would make the scope tighter and make it easier to judge whether the method actually answers the question.

The student justifies the use of a simulation well by linking it to control of variables and repeatability. This is good methodology thinking because it shows informed selection of a method that suits the research problem better than uncontrolled live throws.

The simulation is named but not explained. The student should briefly describe what model the GeoGebra tool uses, what variables it accepts, and why it is suitable for a spinning American football; otherwise the method reads like a black box.

What evidence justifies the expectation that the optimum angle should approach exactly $45^{\circ }$? The student could strengthen the hypothesis by linking it more explicitly to the drag model rather than to the no-drag projectile result.

The range equation is stated with an incorrect factor earlier in the derivation, so the underlying physics needs checking. The student should verify every step of the derivation carefully, because a small algebraic error weakens later conclusions built on it.

The student shows solid subject knowledge by connecting the no-drag case to the standard projectile model. This helps establish a physics baseline before introducing drag and temperature effects.

This explanation is too broad. Drag depends on the speed and orientation of the ball, not simply on the components separately in the way described here. The student should tighten the physics explanation so it reflects the vector nature of drag more accurately.

The student successfully derives a relevant density relationship from the ideal gas law and uses it to connect temperature to air density. This is a strong application of physics content because it directly supports the investigation’s independent variable.

The Magnus-effect explanation is oversimplified and internally uncertain. The student should distinguish more clearly between spin stabilisation, wobble, and sideways force from pressure differences, because the current wording mixes these concepts and weakens the precision of the science.

It would strengthen the knowledge base to explain why $C_D=0.06$ is appropriate for the chosen model and what physical assumptions produce that value. A brief justification would make the later simulation inputs more convincing.

This justification is not fully convincing. The student should explain why a quadratic is the best empirical fit to the observed data rather than rejecting trigonometric forms on symmetry alone, since the physical relationship is not automatically quadratic.

The student is making an analytical choice rather than fitting data blindly, which is a positive sign of critical thinking. Even though the justification could be improved, the attempt to match the model to the physical situation is appropriate.

The analysis overstates what the regression proves. The student should avoid saying the equations show the “exact balance” unless the model has been validated independently; the fitted curve describes the simulated data, not a universal physical law.

The student uses differentiation to verify the vertex mathematically, which is a strong analytical step. This supports the graphically identified optimum and shows good method–analysis linkage.

This conclusion is too strong for deterministic simulation data. The student should distinguish between a high correlation in the fitted outputs and genuine experimental reliability, because a near-perfect line here is partly a consequence of the model design.

What does this ratio actually measure in relation to the research question? The student could strengthen the argument by explaining why introducing $K$ adds insight rather than additional complexity.

The evaluation here partly explains the anomaly, but it still treats the trend as linear despite the irregular points. The student should discuss whether the selected metric is stable enough to support a linear conclusion, or whether the deviations undermine the claim.

This is a strong piece of evaluation because it identifies a specific source of error and explains why small fitting differences have a large effect after differentiation. That shows genuine awareness of how uncertainty propagates through the analysis.

A stronger evaluation would separate the physics limitation from the real-world claim. The student could propose a specific way to model changing $C_D$ across the flight, or at least explain how much effect a small change in spin would have on the predicted optimum angle.

The conclusion does connect the findings back to the real-world context, which helps the argument feel purposeful. The student clearly tries to move from model to application, showing the investigation has an authentic physics focus.

The table of contents lists section pages, but the report should be checked for consistency against the final page numbering and internal references. The student should make sure every section title and page number matches exactly throughout the report.

The report has a conventional, easy-to-follow structure with clear sections from introduction through bibliography. This helps the reader navigate the investigation and shows awareness of standard report organization.

It would improve presentation if the table caption more clearly stated the units and the number of significant figures being used. That would make the data easier to interpret at a glance and reduce ambiguity.

Several figures and tables are numbered inconsistently across the report, which makes them harder to reference clearly in the analysis. The student should use one continuous numbering system for all figures and tables so the discussion can point to them unambiguously.

The student keeps the data presentation organized by summarising the relationship between temperature, air density, and optimum angle in one place. This is effective presentation because it consolidates the key results for the reader.

The graph title is informative because it states the variables being compared and the physical condition being tested. That is good presentation practice because the reader can understand the purpose of the visual immediately.