IB Chemistry HL Internal Assessment Example

The research question is articulated clearly within a specific and relevant context, linking practical applications and polymer chemistry to justify the investigation’s significance.

The introduction provides strong context by detailing real-world uses of sodium polyacrylate and its absorption capacity, effectively grounding the research in practical applications.

The background section explains polymer structure but lacks explicit linkage to temperature‐dependent swelling mechanisms; include a clear molecular rationale for temperature effects.

The hypothesis is grounded in kinetic theory but could be refined by specifying how crosslink disruption contributes to swelling at higher temperatures.

The rationale for choosing three repeats and a 5 min swelling time is stated but lacks justification of their sufficiency to ensure statistical reliability; explain why these parameters were adequate.

The selection of temperature intervals (10–70 °C) is stated but lacks justification for step size; explain why these specific increments were chosen.

The materials list omits polymer purity or molecular weight information; include grade and manufacturer details to enhance experimental reproducibility.

Ethical and environmental issues are acknowledged, but disposal protocols remain general; propose specific eco‐friendly disposal or polymer recycling methods.

The controlled variables are listed with clear rationales and methods, facilitating reproducibility by ensuring only temperature changes affect the results.

The cooling protocol for low‐temperature trials is described but ambiguous; specify exact timing and fridge conditions to ensure consistent sample temperatures.

The filtration and mass‐recording step lacks detail on how residual water is removed consistently; standardize filtration time or method to improve reproducibility.

Raw and processed data are organized in well‐labelled tables with uncertainties, demonstrating clear and precise communication of measurements.

The calculation in the example misplaces the decimal in swelling capacity (reports ~8235 % instead of ~102 %); re‐evaluate the numerical steps in $$SC\%=\frac{(Ws-Wd)}{Wd}\times 100$$.

Uncertainties are propagated uniformly as ±1.02 % for all trials without accounting for varying ranges; recalculate uncertainties using correct error‐propagation for each dataset.

The summary table shows relative uncertainties but some entries appear inconsistent with raw data ranges; verify each percentage calculation against its absolute uncertainty.

The discussion of $$R^2=0.7152$$ notes moderate strength but lacks critique of the linear model’s suitability; consider residual analysis or alternative fits.

The linear graph’s y‐axis uses a compressed scale and lacks clear unit labels; expand the scale and annotate axis units to improve readability.

The logarithmic model yields $$R^2=0.7583$$ but model comparison lacks statistical testing; perform an ANOVA or Akaike information criterion to choose the best fit.

The comparison to Liu & Guo (2001) is well integrated but remains qualitative; include quantitative comparisons of swelling capacities to strengthen the context link.

The concluding discussion addresses the overall trend but omits the significant dip at 50 °C; explicitly reference this anomaly and its implications.

Random errors such as human reaction time and thermometer precision are identified with impact assessed as minimal, demonstrating insightful evaluation.

The specific weakness of final mass measurement bias is described with clear impact on results and a precise mitigation strategy, reflecting top‐band evaluation.

Filtration inconsistencies are identified and the proposal to standardize filtration timing is well‐targeted to reduce variability in water retention.

The identification of heat loss/gain during water transfer as a systematic error is precise, and re‐measuring temperature immediately before pouring is a realistic mitigation.

The suggestion of using a magnetic stirrer to improve mixing uniformity directly addresses inconsistent mixing, offering a realistic and relevant improvement.