IB Psychology SL Internal Assessment Example

The student makes a clear and relevant link between theory and the investigation. This is effective because it shows exactly why the Loftus and Palmer study supports the present research question about how verb choice shapes memory recall.

This is a strong starting point, but the explanation would be more precise if the student separated Bartlett’s schema-based reconstruction from Loftus and Palmer’s post-event misinformation effect. Making that distinction would sharpen the theoretical framing and avoid blending related but different explanations of memory distortion.

The research hypothesis is directional and operationalized, so it can be tested directly. The student has also linked the predicted effect to the IV and DV in a way that is fully appropriate for an SL investigation.

The aim is focused and clearly stated. By specifying the relationship between verb intensity and recall, the student gives the investigation a precise direction that makes the study easy to follow and aligns well with the later hypothesis.

The IV is clearly identified and operationalized through the two specific verbs, which makes the comparison measurable. This level of precision is important because it allows the hypothesis and later analysis to match the actual experimental conditions.

The relevance is well explained through real-world applications to driving and eyewitness testimony. This works because it shows why the investigation matters beyond the classroom and connects the topic to the target group in a meaningful way.

The null hypothesis is stated clearly and matches the operationalized variables. This is good practice because it gives the statistical test a proper comparison point and shows awareness of inferential reasoning.

How fully can an independent-measures design prevent demand characteristics if participants still notice that the task concerns speed estimates after a crash video? A brief acknowledgement of this limitation would make the justification more convincing.

The research design is explained rather than merely named. The student links the choice of an independent-measures design to order effects, which shows methodological understanding and helps justify why this design suits the question.

The sample is described concretely, which helps the reader judge the context and likely generalizability. The student also gives relevant participant characteristics and exclusion criteria, which strengthens the transparency of the sampling section.

The allocation procedure is clearly described and supports fairness between conditions. This is useful because it reduces the chance that one group is systematically advantaged or disadvantaged before the task begins.

The student could strengthen this by explicitly naming the sampling method as opportunity/convenience sampling. That would make the methodology more precise and help distinguish participant recruitment from random allocation.

The control of materials is clearly explained, and the student shows why standardization matters. This is effective because it demonstrates how the questionnaires were kept comparable while manipulating only the IV.

This claim is too absolute. The student could improve accuracy by saying the setup was intended to reduce experimenter bias, since researcher presence can never completely eliminate subtle cues or inconsistencies.

The procedure is detailed enough to be replicable, which is a major strength of exploration. Repeating the video and using a shared projector help standardize exposure across participants.

The ethical consideration is relevant and practical. The student shows awareness of confidentiality and anonymity, which is important in school-based research and supports responsible data collection.

The findings are stated clearly and the descriptive statistics are used appropriately to summarize the pattern in the data. This works well because it directly compares the two conditions and prepares the reader for the inferential result.

The labelling is clear and the figure is tied to the descriptive statistics. This makes the graph useful for communication, not just decoration, because it supports the written interpretation of the results.

The graph addresses the hypothesis directly by comparing the two conditions and displaying variability as well as central tendency. That combination helps the reader see both the direction of the effect and how spread out the responses were.

The decision rule would be clearer if written in the standard form: reject $H_0$ when $p<\alpha$. Rephrasing it that way would improve mathematical precision and reduce the chance of confusion when interpreting the test.

The inferential test is appropriate for the design and the student explains why it was chosen. This shows sound statistical reasoning and helps the reader understand that the test matches the structure of the data.

What other explanation could account for the larger spread in the smashed condition besides verb intensity? Considering alternative causes would make the interpretation more analytical and less speculative.

The statistical conclusion is correct and clearly linked to the test outcome. The student uses both the p-value and the alpha level to justify rejecting the null hypothesis, which is exactly what is needed at this stage.

The finding is interpreted and explicitly linked to the hypothesis. This is strong analysis because it does not stop at statistical significance; it explains what the significance means in relation to the research question.

This is a well-justified modification because it is directly tied to a specific limitation: possible misunderstanding of the questionnaire. The student explains the purpose of the change, which makes the suggestion practical and clearly improvement-focused.

The modification is relevant and clearly linked to a limitation already identified. This works well because it shows an understanding of how participant differences can affect outcomes and how design changes can address them.

This point is relevant, but it stays a little general. The student should explain how perceptual-skill differences would specifically change speed estimates in this task, so the limitation is more directly tied to the hypothesis and data pattern.

The student gives a relevant evaluation of the procedure and materials by linking standardization to reliability. This is effective because it shows not just what was controlled, but why those controls strengthen the investigation.

The student could make this more evaluative by clarifying exactly what is meant by temporal validity here. For example, they could explain whether the 2026 classroom replication strengthens relevance because the effect still appears in a new context, or whether that claim needs stronger justification.

As written, this would only allow post-hoc analysis; it would not guarantee equal representation. The student could strengthen the modification by explaining how gender balance would be achieved at sampling stage, or by phrasing it as a control variable rather than a questionnaire item.

The limitation is relevant because it connects a sample characteristic to possible variation in the dependent variable. That makes the evaluation more convincing than a generic list of weaknesses.

The conclusion does more than restate the result: it links the findings back to the underlying model of reconstructive memory. This is strong evaluation because it shows the student understands the broader significance of the study.