IB Geography HL Internal Assessment Example

Strong fieldwork question: it is clearly geographical, framed around a recognised river model, and focused on a measurable long-profile change. The student can now build hypothesis-led analysis directly from this wording, which is exactly what Criterion A rewards.

Good location specificity here: the student identifies a real river, a district, and practical access conditions that make primary data collection feasible. This helps show that the investigation was grounded in an actual fieldwork setting rather than a generic river study.

Consider adding a simpler inset map with cleaner cartographic conventions: consistent figure numbering, a clearer legend, and a less crowded layout. That would make the spatial pattern of the ten sites easier to interpret and would strengthen the geographical context.

This map is too broad for the research question on a specific river profile. A stronger locational map would zoom in on the Kui Buri River corridor and clearly distinguish the exact field sites, because Criterion A values precision that supports primary investigation.

The definition here is technically incorrect: rotations per minute is a probe reading, not the velocity itself. The student should state how probe spins were converted into a velocity measure and then write the correct equation, otherwise the method becomes scientifically unclear.

Strong methodological choice: the student names a relevant sampling strategy and explains why it suits a river transect investigation. The link to repeated measurements every 50 cm shows purposeful fieldwork design rather than a vague list of procedures.

If accessibility determined site choice, how might that have biased the longitudinal profile? The student should consider whether the easiest sites to reach also happen to be the most disturbed, because that would affect how representative the transect is.

This explanation is too general to show clear theoretical alignment. The student should specify exactly how the poles were used in the cross-section process, because Criterion B expects methods to be described in a way that can be replicated and evaluated.

This is a good example of a method matched to the variable being measured. Using a chain for wetted perimeter is appropriate because it follows the channel boundary more closely than a straight tape, which improves the relevance of the data collected.

The correlation notation is inconsistent and the expression in brackets is unclear. The student should present the coefficient in one correct form and explain how it was derived, because convention errors like this weaken confidence in otherwise strong data treatment.

Strong presentation of relevant processed data: the graph is directly tied to the investigation question and is immediately interpreted in relation to downstream efficiency. The student also uses the graph to support a specific geographical claim rather than leaving it as a standalone visual.

This is effective data treatment because the student clearly links the presentation to the sub-hypothesis and interprets the pattern using river-process terminology. The result is a dataset that is not just shown, but actively used to build analysis.

The graph is interpreted as if it cleanly represents all three axes, but the presentation is harder to read because the values are layered together. The student should make each axis easier to distinguish, so the reader can see how the processed data actually support the trend.

What evidence in the analysis actually justifies the claim that the results 'have not occurred by chance'? The student should think carefully about significance, because overclaiming statistical certainty makes the conclusions look stronger than the evidence supports.

The student uses an observed pattern to support the argument and then attempts to explain a local anomaly using field conditions. This is a productive analytical habit because it shows the data are being interpreted geographically rather than merely summarised.

This interpretation is weakened because the units and starting value are not clearly handled. The student should explain what the probe readings represent and why a value of 0 appears at Site 1, otherwise the trend risks being overstated or misunderstood.

Good analytical linkage: the student does not just describe the graph, but explicitly connects the trend to the Bradshaw model and the investigation question. That direct interpretation is what lifts analysis beyond simple data reporting.

How far is site 6 an anomaly, and how far does it suggest the model itself is incomplete for this river? The student should consider whether the deviation reflects local morphology, measurement issues, or a limitation of the Bradshaw model's assumptions.

The correlation value is incorrect: $r$ cannot be 9.38. The student needs to correct this immediately and ensure that any statistical claim matches the calculation shown earlier, because this is a major analytical accuracy issue.

This conclusion is clear and well supported by the preceding analysis. The student synthesises all three sub-hypotheses rather than repeating graph descriptions, which is exactly what a strong conclusion should do.

The conclusion is undermined by the incorrect correlation value. The student should revise the numerical support so the conclusion accurately reflects the analysis, because conclusions must be fully consistent with the evidence they summarise.

A stronger conclusion would briefly weigh the extent of the match against the model, not just state that it follows it. The student could add one sentence explaining which variable aligned best and which showed the most deviation, making the final judgement more nuanced.

This is a sensible suggestion, but it is still too vague to count as a fully developed evaluation. The student should explain which specific measurements would benefit from the extra personnel and how that would reduce error or improve reliability.

These improvements are relevant and practical because they target the exact problems identified in the analysis. The student explains how each change would improve interpretation, which shows real evaluative thinking rather than simply naming a weakness.

Strong evaluation focus: the student identifies a relevant limitation and links it directly to the river system under study. This is more effective than a generic weakness list because it shows the evaluation is grounded in the actual fieldwork context.

This is a promising evaluative idea, but it needs sharper specificity. The student should name what kind of alternative model or framework would better fit the river, and explain exactly how it would improve the investigation's geographical validity.