IB Geography HL Internal Assessment Example

This gives a precise spatial context with coordinates and a coastal setting, which makes the investigation feasible for primary data collection. The geographic specificity supports the fieldwork question well.

The fieldwork question is clearly geographical and investigable, and it identifies three measurable variables. The explicit link to dune formation helps the student form testable hypotheses rather than just describing a location.

The map would be stronger if it showed a clearer locator hierarchy from Kenya to Kilifi to Mambrui with cleaner labels and a more conventional scale. The student should ensure the map directly helps the reader orient the sampling site rather than only naming places.

This map is relevant, but it does not show the actual transects or sampling points used in the investigation. For a stronger geographic context, the student should plot the fieldwork locations and sampling coverage so the spatial design is immediately visible.

How can the student justify the direction of this hypothesis more carefully, given that lower pH means higher acidity? A clearer distinction between pH and acidity would make the theoretical link much more precise.

This is a sensible method for a coastal dune study because transects perpendicular to the shoreline capture change across the dune profile. The student has chosen a design that matches the geography of the question.

The sampling strategy is not internally consistent because the spacing changes sharply from 10 m to 80 m without explanation. The student should justify why the interval changes and explain how that affects comparability across the transect.

The wind-speed method is too vague to be reproducible because the measurement height is not stated and the phrase 'above the head' is not standardised. The student should specify a fixed height and consistent exposure conditions so readings can be compared reliably.

A stronger method would specify how the random points were generated and how the same locations were matched to the other variables. That would make the vegetation data easier to compare with wind and pH measurements.

This conflicts with the earlier description of 10 m intervals, so the sampling design is unclear. The student should align the stated intervals across all methods to show a coherent investigation plan.

What steps were taken to calibrate the pH meter before fieldwork? Including calibration details would strengthen confidence in the accuracy of the soil pH data.

The student provides raw data with repeated readings and averages, which is a solid foundation for analysis. This allows the reader to check patterns rather than relying only on the graph.

The table is useful, but the wind-direction results are not analytically developed anywhere, so part of the collected information is left unused. The student should either analyse direction as an additional control factor or explain why it is not central to the investigation.

This table is relevant, but the method for measuring dune height is not clearly documented earlier, which limits confidence in the data. The student should explain exactly how dune height was measured and ensure the same method was used at every site.

Including a regression equation and $R^2$ value strengthens the presentation because it quantifies the relationship rather than only describing it visually. This helps the reader judge the strength of the vegetation trend.

The trend is plausible, but the table alone is not as persuasive as a graph would be for showing the relationship between vegetation cover and dune height. A scatter graph with a line of best fit would make the pattern easier to interpret quantitatively.

The explanation would be stronger if it carefully distinguished between acidity and pH: a decrease in pH means increasing acidity. The student should use the correct terminology consistently so the interpretation is scientifically precise.

The Spearman table contains inconsistent variables and values, including a mismatch between the pH table and the ranked data used here. The student should recalculate the test using one consistent dataset and show the ranking process clearly to avoid undermining the analysis.

Does the evidence actually show causation, or only association with distance inland? The student should reflect on whether distance from the shore may be the main driver linking wind, vegetation, pH, and dune height.

The interpretation becomes too certain when it claims the hypothesis is 'fully supported' despite anomalies and a confounding distance gradient. The student should qualify the claim and distinguish correlation from proof of causation.

This is a strong piece of analysis because it links a specific data trend to the hypothesis and explains the geomorphic mechanism. The student is not just describing the graph but interpreting what the pattern means for dune formation.

This is effective analysis because it identifies the overall pattern and connects it to the research question. The student also uses the regression result to support the interpretation rather than relying on description alone.

The anomaly is identified well, but the explanation is still speculative and not tied to field evidence. The student should support anomaly explanations with observations from the site, such as exposure, salinity, or substrate conditions.

The wording overstates what the data can prove. The student should use more cautious language, such as 'suggests' or 'indicates,' because the relationship may also be shaped by distance inland and other unmeasured factors.

The analysis would be stronger if it explicitly separated the chain of relationships: distance to pH, pH to vegetation, and vegetation to dune height. Breaking the argument into linked steps would make the causality clearer.

This Spearman result is not supported by the working shown, so the statistical conclusion is unreliable. The student should recalculate the coefficient carefully and check that the ranked values, ties, and totals are consistent with the raw data.

The conclusion is too general and does not directly address 'to what extent' or rank the relative importance of the variables. The student should state which factor appears strongest and qualify the result using the main limitation of distance from the shore.

The conclusion returns to all three variables and provides a clear overall answer to the fieldwork question. This gives the reader a coherent sense of what the investigation found, even if some of the evidence needs tightening.

The evaluation appropriately starts by naming the investigation’s main strengths and links them to the variables studied. This shows the student is reflecting on the method rather than listing generic positives.

This limitation is relevant, but the evaluation should explain more precisely how rainy conditions would alter each variable. The student should connect the limitation to wind speed, soil moisture, pH, and vegetation cover individually.

This is a good evaluative transition because it signals a balanced assessment. The student is structuring the reflection in a way that separates strengths from limitations clearly.

This is a strong practical suggestion because it directly addresses subjectivity in estimating vegetation cover. The student should also explain how the point-intercept method would improve consistency across all sampling locations.

This is a relevant improvement, and it would be even stronger if the student specified how many repeat days, transects, or samples would be collected. Clear sampling numbers make an improvement plan more convincing and more realistic.

The issue is valid, but the explanation needs greater technical precision. The student should specify an improved sampling duration and explain how repeated timed measurements would reduce short-term wind variability.