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Chemistry IA Exemplar: Water Bath Temperature and Ethanol Oxidation… | RevisionDojo
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IB Chemistry HL Internal Assessment Example
How do varying water bath temperatures (15℃, 20℃, 25℃, 30℃, 35℃) influence
the oxidation rate of ethanol by potassium permanganate in a basic medium, as
measured by red light absorption at 650 nm?
4
Official IB Result
13/24
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13/24
0
12
24
5.1·Suggestion
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The oxidation pathway figure lacks descriptive step labels. Add clear annotations for each half-equation stage to improve reader comprehension.
Criteria A: Research Design
5/6
0
3
6
Criteria Strands
Excellent
Research question context
Excellent
Methodological considerations
Good
Methodology description
Criteria Feedback
Research question is framed within a specific, real-world context and quantitatively precise.
Methodological considerations (volumes, concentrations, replication, equilibration) are thoroughly discussed.
Procedure detail is sufficient for reproduction with only minor clarifications needed.
Ambiguity remains in mixing and cuvette-blanking protocols at reaction temperature.
Minor formatting and unit inconsistencies in half-equation balancing and molarity calculation.
Repetition of the research question later in the text is stylistic rather than substantive.
1.1·Strength
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The research question is quantitatively framed within the context of ethanol oxidation by KMnO₄ in basic conditions, clearly linking temperature variation to red light absorption at 650 nm.
1.2·Strength
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The introduction effectively situates KMnO₄ in wastewater treatment and justifies targeting ethanol oxidation, demonstrating strong real-world relevance.
1.3·Weakness
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The half-equations are presented, but the balancing steps are compressed into one line, reducing clarity. Expand the balancing process to enhance reproducibility.
1.4·Suggestion
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Avoid restating the research question verbatim later; instead, integrate reminders of its context in the discussion to maintain focus and conciseness.
1.5·Strength
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Controlled variables are comprehensively listed with volumes, concentrations, order of mixing, equilibration time and temperature monitoring, supporting reproducibility.
1.6·Strength
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Materials list includes uncertainties for pipettes and balance, enhancing reliability of data collection.
1.7·Weakness
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Absorbance measurement timing is described, but the calibration zeroing procedure at reaction temperature is not. Clarify cuvette blanking protocol.
1.8·Suggestion
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Specify how test tubes are mixed (e.g., inversion, stirring) during equilibration and sampling to remove ambiguity in the methodology.
1.9·Weakness
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The KMnO₄ molarity calculation shows “\overline{mol}” incorrectly; ensure units are consistent (mol) and symbols properly formatted.
Criteria B: Data Analysis
4/6
0
3
6
Criteria Strands
Excellent
Communication of data recording and processing
Moderate
Consideration of uncertainties
Good
Data processing quality
Criteria Feedback
Data tables and graphs are clearly labeled with units and uncertainties.
Calibration curve construction and regression are well justified and applied.
Consideration of uncertainties is uneven: error bars are missing and some instrument uncertainties are not propagated.
Outlier treatment lacks statistical testing and discussion of its impact on results.
Several unit slips and a mistyped rate equation reduce the polish and precision of the analysis.
2.1·Strength
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Construction of the calibration curve is clearly described, including concentration series and regression, enabling accurate conversion of absorbance.
2.2·Suggestion
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Include details on the number of replicate measurements used to construct each calibration point to quantify associated uncertainties.
2.3·Strength
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Presentation of processed average absorbances with uncertainties in Table 2 is clear and precise, aiding interpretation.
2.4·Weakness
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Error propagation example omits propagation of colorimeter uncertainty; include both instrumental uncertainties for full combined error.
2.5·Weakness
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The outlier in Trial 5 at 20 °C is noted but lacks any statistical treatment (e.g. Grubbs’ test); discuss its impact on average and consider consistency checks.
2.6·Strength
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Qualitative observations in Table 3 complement quantitative data by describing MnO₂ precipitation and color changes, demonstrating thorough data recording.
2.7·Weakness
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The text states r is obtained by taking the square root of variance, which is incorrect—the correlation coefficient is directly derived by regression; clarify terminology.
2.8·Suggestion
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Discussion attributes the negative correlation to increased collision frequency; reinforce with reference to activation energy and Arrhenius equation.
2.9·Strength
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The logarithmic calibration model is well justified by the high r² value and is appropriately applied to convert absorbance to concentration.
2.10·Weakness
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The rate equation description in Text/2 is mistyped and unclear; provide the correct formula as Rate = (Initial – Final [KMnO₄]) / time.
2.11·Weakness
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Error propagation section summarizes combined uncertainties but omits full calculation steps for pipettes and balance; include detailed propagation for each tool.
Criteria C: Conclusion
2/6
0
3
6
Criteria Strands
Good
Conclusion relevance and support
Moderate
Scientific context comparison
Criteria Feedback
Conclusion restates the observed temperature–rate trend and links it to collision theory.
Findings are connected to practical water-treatment considerations, showing context awareness.
Mechanistic justification of absorbance–rate relationship is accepted rather than critically argued.
Comparison to external studies lacks quantitative detail or critical analysis.
Opportunities for deeper discussion (energy trade-offs, matrix effects) are not explored.
3.1·Suggestion
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To strengthen application, discuss trade-offs between energy input for heating and improved oxidation efficiency.
3.2·Strength
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Discussion applies findings to water treatment optimization, demonstrating relevant comparison to scientific and industrial context.
Criteria D: Evaluation
2/6
0
3
6
Criteria Strands
Good
Methodological weaknesses
Moderate
Suggested improvements
Criteria Feedback
Student identifies realistic methodological weaknesses (detector saturation, evaporation, model limits).
Practical improvements (dilution, lower concentration, quantifying evaporation) are appropriate.
Impacts of weaknesses are discussed only qualitatively without quantification.
Suggested improvements lack implementation details and rationale depth.
Relative importance of each limitation is not evaluated.
4.1·Suggestion
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Evaluation identifies relevant weaknesses but could quantify their relative impact on reaction rate (e.g., percent overestimation due to detector saturation).
Future improvements should include a method to quantify ethanol evaporation (e.g., gravimetric loss measurement) to refine error analysis at higher temperatures.
