IB Geography SL Internal Assessment Example

The fieldwork question is clearly geographical and focused on a place-based retail issue. Framing the task around “to what extent” also creates scope for hypothesis testing and comparison, which is a strong foundation for a GIS/urban fieldwork investigation.

The syllabus links are too broad here. The student names options, but does not clearly develop concepts such as accessibility, retail hierarchy, range, threshold, or sphere of influence into the question. Making those theoretical links explicit would strengthen the geographic framing.

This gives a clear location anchor and shows why the study is feasible in a real urban setting. The student establishes a local context that can be investigated through primary data rather than remaining at a vague national scale.

The locational mapping is strong because the study identifies the exact shopping centres being investigated. This helps the reader understand spatial relationships immediately and supports fieldwork feasibility.

The student could strengthen the context by explicitly linking each location characteristic to a theory-based expectation, such as why a transport node or central district should increase footfall. That would turn description into more analytical geographic context.

The student could improve this map by making the accessibility logic clearer: for example, showing which bus stops were counted within the stated distance buffer and labelling key transport corridors more precisely. That would make the geographic reasoning easier to follow.

This hypothesis is understandable, but it remains only loosely tied to theory because “city centre” and “young people” are not operationalised. The student should define how age and centrality will be measured so the claim can be tested more rigorously.

What geographic concept is being tested here, and how could the student define it more precisely so the hypothesis becomes easier to measure and compare across centres?

The student should also explain how anonymity helped the data quality, not only the ethics. For example, they could discuss whether anonymity encouraged more honest answers and whether the online format may have altered who responded.

The secondary data source is relevant, but the procedure is too vague. The student should explain exactly what was observed, how it was recorded, and whether the same criteria were applied to every centre to ensure comparability.

This is a useful overview because it shows that the questionnaire was designed around the investigation’s core variables. The student is clearly collecting data that can speak to popularity, accessibility, and preference rather than gathering unrelated information.

The sampling description is problematic: convenience sampling is acknowledged, but the student then describes the sample as “random,” which is not the same thing. The method should be stated consistently, and the implications for bias should be made explicit.

This overstates the representativeness of the sample. A convenience sample of 97 respondents can be useful, but it cannot automatically be treated as representative of all shopping-centre users in Lublin without stronger sampling controls.

Grouping survey questions by hypothesis is a clear methodological strength. It shows the questionnaire was intentionally designed to generate evidence for specific lines of enquiry rather than being a generic survey.

Why was 500 m selected as the cut-off point, and would the conclusion change if the student used a different buffer distance such as 250 m or 800 m?

This gives the accessibility measure a concrete operational definition, which is exactly what strong methodology needs. The student is not just saying “nearby bus stops” but quantifying the distance used in the investigation.

This interpretation mixes transport-use data with parking preference data without showing how one causes the other. The student should separate the two variables more carefully or use cross-tabulation to demonstrate whether car users are actually the group influenced by parking availability.

The student says the table is used to establish a correlation, but no actual correlation test is carried out. At this stage the evidence is descriptive only, so the wording should stay cautious unless a statistical association has been demonstrated.

This is a useful anomaly, but the explanation needs stronger evidence. The student suggests location in the city centre as the reason, yet that claim should be supported with direct data rather than treated as the explanation by default.

This is a strong comparative statement because it uses the table and graph evidence together to build a plausible link between accessibility and popularity. The student is moving beyond listing data and beginning to compare centres directly.

This table is highly relevant because it turns a broad idea like “better communication” into measurable comparative data. The student uses a sensible format for linking accessibility features to the shopping centres being studied.

The data presentation is being interpreted accurately, but the wording should be checked carefully because the percentage is extremely dominant and may indicate a youth-skewed sample rather than a balanced age profile. The student should discuss how this affects the validity of later conclusions about “young people.”

The student is drawing a direct link between the graph and the hypothesis, which is appropriate for this criterion. The analysis is anchored in the displayed data rather than drifting into unsupported generalisation.

This conclusion goes beyond what the data can prove. A high proportion of cinema use does not by itself establish that cinema presence caused mall choice, so the student should phrase this as an association rather than a demonstrated cause.

How could the student use this graph more analytically to show whether the most popular shop types actually match the centres with the highest popularity ratings?

The anomaly is identified well, but the explanation is speculative. The student should either provide evidence for the claim about older infrastructure or present this more cautiously as a possible reason rather than a settled one.

This is one of the strongest links between evidence and interpretation in the report. The student compares ratings with the stated preference factor, which helps show how different datasets support the same pattern.

The conclusion stays focused on the actual hypothesis and brings in age, facilities, and centre location together. That keeps the response clearly linked to the investigation rather than becoming a generic summary.

This conclusion only partially answers the hypothesis. The student reports that accessibility matters, but does not clearly weigh how important it was compared with location, parking, or the demographic composition of respondents.

The student could strengthen the conclusion by explicitly stating what this mismatch means for the research question. For example, is popularity better explained by convenience than by facilities, or do facilities matter only after accessibility has been satisfied?

The conclusion broadens into transport and location, which is reasonable, but it still does not fully answer the “to what extent” part of the question. The student should make a clearer judgement about whether facilities were the main driver or only one factor among several.

The map is useful as a summary device, but the conclusion still needs a clearer final judgement drawn from it. The student should state which factor or combination of factors was most influential overall, rather than only listing positive and negative influences.

A stronger conclusion would quantify the extent of support more explicitly. The student could say whether the hypothesis was mostly supported, partly supported, or only weakly supported, and then justify that judgement with the key pieces of evidence.

This is a strong concluding insight because it recognises an important distinction between preference and actual use. That nuance improves the quality of the overall argument and shows the student is synthesising findings rather than simply restating them.

The student could improve this point by naming what kind of comparison study would be useful and how it would test the findings. For example, a parallel survey in another Polish city could show whether the same accessibility-pattern relationship appears elsewhere.

This is a relevant and honest evaluation of a major methodological weakness. The student identifies a genuine issue and connects it to the design of the investigation rather than offering a superficial comment.

The limitation is identified, but the effect on the conclusions is not fully developed. The student should explain how under-representing older respondents may have shifted the results toward youth preferences and influenced the ranking of centres.

This improvement is relevant, but it would be stronger if the student also explained how the sampling method would change. For example, a stratified or quota sample across age groups and shopping centres would make the dataset more defensible.

The student correctly identifies the absence of open questions, but the evaluation stops short of explaining why that matters. The report should note that without qualitative responses, it is harder to understand the reasoning behind preferences and ratings.