IB Sports, exercise and health science (SEHS) SL Extended Essay Example

The topic statement is not fully aligned with the investigation because the report later measures 800 m running performance rather than muscle strength. The student should revise the topic so it matches the actual dependent variable, or else explain how strength is being operationalised and measured.

The research question is focused, but the wording is awkward and mixes "performance," "running time," and later "speed." The student should choose one operational measure and use it consistently throughout the essay so the question clearly matches the data analysis.

This opening gives the investigation a clear sports-science rationale by linking 800 m performance to both energy systems. That helps the reader immediately understand why plyometric training is being considered for this event.

The research question is stated explicitly and includes the intervention duration, population, and event distance. This makes the scope of the investigation easy to follow and gives the methodology a clear target.

The student identifies a specific experimental design and links it directly to the proposed causal question. This is strong method communication because it tells the reader how the investigation is intended to answer the research question.

The methodology claims stratified randomization, but the allocation process is not actually described. The student should explain exactly how participants were stratified and assigned, because without that detail the validity of the claimed RCT design is hard to judge.

This is a relevant and conceptually sound use of sports-science evidence. It supports the essay’s rationale by showing that 800 m performance depends on a mixed energy profile, which justifies investigating a training method that may affect both power and efficiency.

This shows accurate subject knowledge and places the investigation within the correct athletic context. The student uses the source to define the event range before moving into more specific physiological discussion.

The student demonstrates good conceptual understanding by linking glycolysis and anaerobic contribution to race phases rather than treating the event as purely endurance-based. This helps the background section stay tied to the performance demands of the 800 m.

This is a strong explanation of the training mechanism being investigated. The student uses appropriate terminology and connects the stretch-shortening cycle to athletic performance in a way that supports the later interpretation of results.

The hypothesis uses "correlation," but the investigation is an intervention study comparing pre- and post-training performance. The student should frame the hypothesis in causal or comparative terms, because correlation is not the right concept for this design.

A stopwatch measures time, not speed. The student should use the correct terminology throughout, since precision in measurement language is part of accurate scientific communication.

The dependent variable is described as "speed," but the raw data later records finishing times. The student should define the outcome as time or convert everything consistently to speed, because mixing the two undermines conceptual accuracy.

The ethical discussion is helpful, but for participants aged 15-18 the student should also evidence parental or guardian consent and, ideally, safeguarding procedures. A PAR-Q alone is not enough to demonstrate full ethical protection for minors.

This is a good attempt to strengthen data quality through repeated observation. The student shows awareness that human timing error can affect results and describes a practical way to reduce it.

The sign of the speed difference is handled incorrectly. If final speed is higher than initial speed, the change should be positive, not negative. The student should recheck the subtraction rule and recalculate all difference scores consistently.

The processed data contain a major inconsistency: the calculation converts time to speed, but several later values and graphs still appear to be in seconds. The student needs to verify every transformation step, because inconsistent processing weakens the reliability of the entire analysis.

The graph title says "speed improvements," but the plotted values on the axis are raw times in seconds. The student should relabel the graph so the variable displayed matches the units shown, otherwise the visual evidence becomes misleading.

The analysis overstates the result by calling a pre-/post-intervention change a "positive correlation." The student should describe this as a change or improvement, not a correlation, because the statistic being shown here is within-subject performance difference.

If the control group also improved, what evidence shows that the gains are due specifically to plyometrics rather than practice, maturation, or the training environment? The student should use the comparison group more explicitly when making causal claims.

The statistical decision rule is stated generally, but the later interpretation must still match the actual p-value and test direction used. The student should keep the null-hypothesis language precise throughout, because small wording errors can change the meaning of the result.

This interpretation is incorrect because $0.238$ is greater than $0.05$, not lower. The student should correct the comparison and then restate the conclusion accurately, since this mistake reverses the meaning of the test result.

The paired t-test interpretation is stronger here, but it still uses "positive correlation" for a before/after change. The student should instead state that the intervention produced a statistically significant increase in performance, which is the more accurate conclusion.

This conclusion goes beyond the evidence because the between-group test did not show a significant advantage for plyometrics over endurance training. The student should soften the claim and distinguish "improved after PT" from "performed best through PT."

This is a relevant and honest limitation. The student correctly links the small sample to reduced generalizability and lower statistical power, which shows meaningful evaluation rather than simple description.

The student identifies a concrete source of measurement error and explains why it matters. This is valuable evaluation because it connects the limitation directly to the reliability of the dependent variable.

This is an oversimplification: error bars show variability or uncertainty, but they do not by themselves prove statistical significance. The student should explain that inferential tests, not the presence of error bars alone, determine significance.

The student makes a thoughtful extension beyond the immediate investigation by proposing additional tests that could triangulate the findings. This shows the ability to think about how evidence might be broadened in future research.

This is a useful evaluative suggestion because it connects directly to the research design and the time frame of adaptation. The student shows awareness that six weeks may not capture longer-term training effects.

The report includes a contents page, which helps the reader navigate the investigation efficiently. This is a strong structural feature because it signals an organised academic presentation.

The student uses conventional sectioning, moving from introduction and methodology into results, discussion, and evaluation. That overall structure is appropriate for an extended essay and makes the line of argument easy to follow.

Including a timeline diagram supports the reader’s understanding of the procedure and sequence of measurements. This is a good presentation choice because it clarifies the experimental flow more efficiently than prose alone.

The student provides a detailed training outline, which makes the investigation more transparent and reproducible. That level of procedural detail is especially useful in a methods section.

The table title is informative, but the table content later mixes figures and units in a way that can confuse the reader. The student should ensure that the displayed variable, unit, and sign convention all match the surrounding text and calculations.

The graph label does not match the values shown, which appear to be times rather than speeds. The student should correct the axis/title wording so the visual presentation supports accurate scientific interpretation.

The statistical table is a helpful way to summarise the inferential test, but the interpretation immediately below it contains a p-value comparison error. The student should align the table summary and written explanation carefully so the presentation of results remains trustworthy.