IB Biology SL Internal Assessment Exemplar: Does the Type of Food We Consume Affect Our Short Term Memorization Skills?

The research question is clear, but it is still very broad. The student should narrow the context by specifying the exact foods, timing, participant group, and the memory measure being used so the investigation becomes more focused and scientifically precise.

The introduction gives the investigation a clear scientific direction by linking diet, blood sugar, inflammation, and memory. This helps justify why the research question matters and shows the student is thinking beyond a simple comparison of foods.

The participant choice is stated, but the method for selecting them is not explained. The student should describe how similarity in recall skills was established and why two participants are enough to answer the question reliably.

A stronger design would include counterbalancing or a crossover arrangement so diet order does not confound the outcome. Repeating the same participant under both conditions would make the conclusion about food type much more convincing.

How was the nutritional content of the pizza standardized across days and across servings? If fat, carbohydrate, and protein content varied, that could affect whether the investigation is really testing the food type rather than meal composition.

The student should explain why one hour was chosen as the delay and why a five-minute random-number task is an appropriate measure of memorization. Justifying these choices would strengthen the methodological reasoning behind the design.

The two diets are described only by mass, not by nutrient composition. Because 300 g pizza and 150 g salad are very different foods, the student should explain how the servings were made comparable for calories, macronutrients, or other relevant variables.

The tables for each condition organize the raw and processed values in a readable way. This layout makes it easier to compare day-by-day trends and overall averages, which is helpful for tracking changes in performance.

The recording terminology is imprecise here. The student should use one consistent unit label and define exactly what the timing column represents so the table communicates the procedure and data more clearly.

This description is still too vague for reliable data processing. The student should explain how the percentages were calculated and what counted as a correct response so the reader can verify the results independently.

The student claims to consider variability, but no actual uncertainty measure is shown. To make this meaningful, the report should include range, standard deviation, or another measure of spread rather than only mentioning variability in words.

The student clearly states the main processing step, which helps the reader follow how raw daily results were turned into summary values. This is a useful foundation for analysis because it shows the comparison was based on aggregated performance, not a single day.

The comparison is described, but the analysis does not yet show a direct statistical comparison between diets. The student should add an explicit between-condition comparison and explain why the observed differences are meaningful rather than just descriptive.

How meaningful is this summary without any spread or statistical test? With only one participant per condition, the mean alone cannot show whether the observed difference is larger than normal day-to-day variation.

The student should show the calculation that produces the 5% change. A worked example would make the processing transparent and would help the reader check whether the percentage difference was computed correctly.

This interpretation is based on one participant’s pattern and cannot support a broad claim on its own. The student should tie the conclusion more closely to the summary data and acknowledge that day-to-day fluctuations may also explain the change.

Does a 99.1% average necessarily prove improvement caused by the salad? The student should think about whether the baseline performance, repeated practice, or individual ability could also explain this outcome.

This conclusion is too strong for the evidence presented. The student should avoid claiming a direct effect from a design with only two participants and several uncontrolled variables; instead, the conclusion should be phrased more cautiously to match the limited analysis.

The student attempts to connect the findings to scientific context, which is an important part of a strong conclusion. Linking results to earlier research helps show that the investigation is not isolated and that the ideas are being placed within a wider evidence base.

The conclusion ends with a relevant forward-looking statement that connects naturally to the research question. This shows the student can extend the investigation beyond the immediate results and identify a sensible broader direction for future work.

The conclusion goes beyond what the data can justify, especially the claim about long-term brain protection. The student should limit the conclusion to the short-term memory task actually studied and avoid extending the findings to long-term effects without evidence.

The student should turn this into a specific evaluation point by explaining exactly how variability affected confidence in the results. For example, identifying whether one or two outlier days changed the mean would make the evaluation much more insightful.

If performance was already close to perfect on several days, how much room was there for improvement? The student should consider whether a ceiling effect might limit how much the salad condition can really demonstrate.

This identifies a possible limitation, but it is still too general. The student should explain which specific weakness caused the unpredictability, such as individual variation, lack of control variables, or the absence of repeated trials, and how that would affect the result.

This is not yet a well-supported methodological limitation. The student should separate experimental limitations from biological explanations and identify what in the method prevented those nutrient effects from being tested directly.

The improvement is realistic, but it is very broad. The student should propose concrete changes to the investigation itself, such as using more participants, counterbalancing the diets, standardizing sleep and caffeine, and measuring nutrient intake.

The student does identify a relevant connection to prior research, which is a useful starting point for evaluation. This helps show awareness that the findings should be interpreted in relation to established scientific ideas rather than in isolation.

A stronger improvement would be a more direct response to the weaknesses in this study. The student could suggest a crossover design, a larger sample, and controls for sleep, exercise, and prior food intake so the same investigation becomes more reliable.