IB Psychology HL Internal Assessment Example

The definition is concise and accurate enough to establish the theory clearly. The student then explains the performance effect, which is important because it shows the model is not just named but understood.

The aim is clear and tightly focused on a specific replication question. Stating both the original study and the performance outcome helps the reader immediately understand what is being tested and why the investigation matters.

The student does well to flag a deliberate methodological adaptation and justify it with the limited sample size. That kind of transparency helps the reader judge the replication's realism and feasibility.

The relevance is explained well here: the student connects the investigation to wider educational and workplace inequality. That link works because it shows how the research question goes beyond the classroom and has genuine social value.

The independent variable is operationalized clearly through the exact statement used. This is strong because it turns an abstract concept into a concrete experimental manipulation.

The null hypothesis is clearly stated in a way that is directly testable. The wording links well to the dependent variable and establishes the statistical baseline for the investigation.

Consider naming the condition more explicitly here, for example by stating that girls exposed to stereotype threat will score lower than girls in the control condition. That would make the directional prediction sharper and easier to match to the analysis later.

The dependent variable is identified in measurable terms, which makes the hypothesis testable. This clarity will help the student keep the later analysis aligned with the aim.

The student identifies the design correctly and explains why it was chosen. Linking the design to reduced demand characteristics shows understanding, not just description.

The materials are listed clearly and linked to their ethical purpose. That kind of structure makes the procedure easy to follow and shows awareness of participant protection.

The sampling method is clearly identified and justified with practical constraints. This is effective because it shows the student understands why the sample was realistic even if it was not ideal.

The participant choice would be clearer if the student explained the role of the boys in relation to the hypothesis and final comparison. As written, the boys' presence is mentioned, but their purpose in the analysis is not fully justified.

It would be stronger to also explain why an independent-measures design is a weaker fit here in terms of individual differences in mathematical ability. That issue is especially relevant to this investigation and would show deeper evaluation of the design choice.

This is asserted too strongly. Having a teacher create the test may improve credibility, but it does not by itself prove the test was unbiased. The student should explain what steps were used to reduce bias in the questions themselves.

The student could improve this by specifying exactly what was controlled, such as noise level, seating arrangement, timing, and lighting. Precise detail would make the control easier to evaluate and replicate.

This control is not fully convincing: passing a lower-level test does not show that the groups were matched for mathematical ability. A stronger control would be to measure prior maths ability directly or use a pre-test so differences between participants are more rigorously addressed.

This is a strong explanation of control because it connects a concrete material to a specific source of bias. The student shows that standardization was used for a valid methodological reason, not simply because it is routine.

The ethics section is clear and relevant, especially because it names informed consent, withdrawal rights, anonymity, and debriefing. That combination shows a solid understanding of the main ethical safeguards.

The figure supports the research question well because it compares the relevant group means directly. The student has chosen a clear visual format that makes the pattern in the data easy to see.

The graph title is informative and directly related to the hypothesis. That helps the reader understand what comparison is being shown without needing extra explanation.

The student correctly interprets the mean comparison in relation to the hypothesis. This is useful because it states the direction of the observed effect before moving on to statistical significance.

The student uses descriptive statistics appropriately to summarise the data before making inferential claims. That sequencing works well because it gives the reader a numerical overview of the groups first.

The interpretation would be stronger if it distinguished between 'did not find support in this sample' and 'does not support the theory' more carefully. A non-significant or opposite pattern does not disprove the theory; it only shows this replication did not produce the predicted effect.

This conclusion is based on an invalid statistical step. Averaging p-values is not appropriate, so the decision about significance needs to be revised using one correctly reported p-value from the test.

The inferential reporting is confused here. Two p-values should not be averaged, and the calculation procedure is not explained clearly enough for the reader to verify the result. The student should report the single test output directly and explain exactly how it was obtained.

The finding is stated clearly and linked to the statistical test. The student also connects the result back to Spencer et al., which is important for showing what the data mean in context.

The student identifies a relevant methodological strength and ties it to internal validity. This works because it shows awareness that controlling extraneous variables helps make the findings more trustworthy.

This conclusion overreaches the evidence. The student should limit the claim to this sample and this procedure, and then discuss possible reasons the replication may have differed from the original study before questioning the theory more broadly.

The modification is relevant and linked to a real limitation. The explanation is useful because it shows how reducing distraction would improve concentration and therefore the quality of the data.

This is a sensible modification, but it would be stronger if the student explained exactly how ability would be measured and how groups would be matched. That would make the improvement more clearly linked to the limitation it is meant to solve.

This limitation is well chosen because it directly affects the fairness of the comparison between groups. The student explains the consequence clearly: unexplained ability differences could distort the mean and weaken validity.

The student explains the limitation well by connecting group differences in ability to participant variability. This is effective because it shows understanding of why independent groups can weaken a comparison study.

The proposed fix is relevant, but it would be better if the student explained whether this would involve pre-testing, matching, or selection criteria. Naming the exact method would make the modification more practical and fully justified.

The student correctly identifies a limitation that affects generalisability and statistical power. This is a strong choice because it is clearly relevant to the confidence that can be placed in the conclusion.

The modification is appropriately linked to the limitation and its effect on representativeness. The student shows a good understanding of why a larger sample would improve the external validity of the investigation.

The evaluation closes by connecting the investigation to wider implications, which gives the work a thoughtful ending. Even though the conclusion is broad, the student does attempt to consider why the result matters beyond the task itself.