To what extent does varying the glycerin concentration (0%, 20%, 40%, 60%, 80%) in water affect the specific heat capacity (J kg-1K-1) of the solution as quantitatively determined by the electrical calorimetry method?SL
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7
Official IB Result
21/24
Criteria A: Research Design
5/6
0
3
6
Criteria StrandsPro
A.1Research question context
Excellent
A.2Methodological considerations for collecting data
Good
A.3Methodological considerations
Good
Criteria Feedback
- The student states a focused, quantitative, and feasible research question with clear independent and dependent variables.
- The student places the investigation in a specific thermal-physics context and explains why it is scientifically and practically relevant.
- The student's method is generally well structured, with preliminary trials, repeated measurements, and controlled apparatus conditions.
- Most of the procedure is detailed enough that another student could follow the overall design.
- The student makes thoughtful methodological choices that show planning and refinement before full data collection.
- The student's explanation of how the efficiency calibration was obtained is not fully developed.
- Using volume percentages rather than mass-based composition creates ambiguity because glycerin and water have different densities.
- Some methodological considerations are described rather than fully explained, especially where they affect the sufficiency of the data.
- The student does not fully address how changing viscosity may affect convection, temperature uniformity, or heat transfer across concentrations.
- A few procedural details are still missing for complete reproducibility, such as how some derived constants and selection steps were established.
1.1·Strength
Page 2
The research question is focused, quantitative, and feasible. The student identifies the IV, DV, and measurement method precisely, which makes the investigation easy to follow and gives the study a strong experimental direction.
1.2·Strength
Page 2
The student situates the investigation in a clear real-world context and explains why the topic is worth studying. This works well because it shows the research question is not isolated from application, which strengthens the rationale for the investigation.
1.3·Strength
Page 5
The inclusion of preliminary trials is a strong design choice because it shows the method was refined before data collection. This improves validity by making the selected heating time and apparatus setup more defensible.
1.4·Weakness
Page 5
The student does not explain how the value of was obtained from the calibration run. To make the method reproducible, the calibration procedure should show the data used, the calculation steps, and why this efficiency can reasonably be transferred to all concentrations.
1.5·Weakness
Page 6
The student should recognise that defining concentration only by volume is methodologically risky here because glycerin and water have different densities. A mass-based preparation would better match the later thermodynamic comparison and reduce ambiguity in what the stated percentages actually represent.
1.6·Question
Page 7
What evidence shows that room conditions were stable enough for this control to be effective across all trials? A brief note on how ambient temperature or drafts were checked would make the control strategy more convincing.
1.7·Suggestion
Page 7
Consider adding an explanation of why constant volume alone is sufficient, or whether constant mass would be more appropriate. Since density changes with composition, clarifying this control would strengthen the logic linking concentration to temperature rise.
Criteria B: Data Analysis
5/6
0
3
6
Criteria StrandsPro
B.1Communication of data recording and processing
Good
B.2Consideration of uncertainties
Moderate
B.3Data processing quality
Poor
Criteria Feedback
- The student's raw data are clearly organised and easy to follow across all concentrations and trials.
- The student shows the main processing steps transparently, including averages and sample calculations.
- The student includes uncertainty information and standard deviations, which shows awareness of reliability.
- The student's processed tables and graphing make the overall trend in the data visible.
- The analysis is logically structured and demonstrates real effort to present the results clearly.
- There is an internal inconsistency in the energy calculation, which affects the reliability of the processed values.
- The student's uncertainty treatment is incomplete because some contributing terms are not fully propagated.
- The graph uses inconsistent units compared with the rest of the analysis.
- The theoretical comparison is weakened by using volume fractions where mass fractions would be more appropriate.
- Some interpretation of the processed data remains too general to be fully precise.
2.1·Strength
Page 12
The raw data are organised clearly across all concentrations and trials. This makes the processing traceable, which is essential because the reader can follow each experimental value into the later calculations.
2.2·Weakness
Page 13
The uncertainty propagation is incomplete because it excludes the calorimeter term even though that contribution is included in the main equation. If a term is said to be negligible, the student should justify that decision quantitatively rather than omitting it outright.
2.3·Weakness
Page 13
The calculation contains an internal inconsistency: does not equal unless the power is 75 W, not 0.75 W. This matters because the error propagates into every processed specific heat capacity value, so the energy substitution must be corrected.
2.4·Strength
Page 13
The sample calculation is helpful because it shows how the mean was obtained from repeated trials. This supports transparency in the processing and allows the reader to replicate the averaging method.
2.5·Question
Page 15
What does the value actually tell the student about the relationship between concentration and specific heat capacity, and what does it not tell them? Reflecting on that distinction would strengthen the interpretation of the graph.
2.6·Suggestion
Page 15
Consider adding explicit uncertainty bars and a brief note on what they represent. That would make the scatter and the line of best fit more informative, especially when comparing how much the repeated trials overlap at each concentration.
2.7·Weakness
Page 15
The graph axis label is inconsistent with the rest of the analysis, which uses . The student should keep units consistent across tables, calculations, and graphs so that the plotted values are interpreted correctly.
2.8·Weakness
Page 15
The theoretical values are based on a mass-specific quantity, but the background defines the model using fractions by volume. Because glycerin and water have different densities, the processing should use mass fractions or justify the approximation explicitly.
2.9·Weakness
Page 16
The student’s explanation of the theoretical graph is too vague to be fully analytical. The discussion should identify which assumptions in the model matter most, such as the use of volume fractions or the assumption of ideal mixing, and explain how each would affect the values.
Criteria C: Conclusion
5/6
0
3
6
Criteria StrandsPro
C.1Conclusion relevance and support
Excellent
C.2Scientific context comparison
Good
Criteria Feedback
- The student directly answers the research question and clearly describes the main trend in the data.
- The student supports their conclusion with numerical evidence rather than only restating the hypothesis.
- The student compares their results with accepted scientific context and prior research, which strengthens the discussion.
- The student identifies that the experimental values diverge more from the theoretical model at higher concentrations.
- The student's conclusion is generally consistent with the pattern shown in the processed data.
- The student's conclusion is a little too definite given the limitations in the method and analysis.
- The comparison to scientific context is relevant but not yet fully detailed or fully matched to the student's exact system.
- Some of the precision in the final claim depends on assumptions that are not completely secure.
- The student could qualify the interpretation more carefully where the method introduces systematic uncertainty.
3.1·Weakness
Page 17
The conclusion is a little too certain given the methodological limitations in the analysis. The student should qualify the claim more carefully, because the precise values depend on assumptions about heater efficiency and the theoretical comparison model.
3.2·Strength
Page 17
The conclusion clearly answers the research question and is tightly linked to the data trend. This works well because it quantifies the change rather than simply restating the hypothesis, making the claim more precise and convincing.
3.3·Weakness
Page 18
The student’s scientific comparison remains somewhat superficial because the cited study is not directly equivalent to this glycerin-water investigation. A stronger comparison would match concentration basis, temperature conditions, and mixture type more closely.
3.4·Strength
Page 18
The comparison to literature is relevant and helps place the results in a broader scientific context. This strengthens the conclusion because it shows the observed inverse relationship is not just isolated to this dataset.
Criteria D: Evaluation
6/6
0
3
6
Criteria StrandsPro
D.1Methodological weaknesses
Good
D.2Suggested improvements
Good
Criteria Feedback
- The student identifies several specific limitations rather than only listing generic weaknesses.
- The student explains why heat loss, viscosity, and efficiency assumptions matter to the validity of the experiment.
- The student's suggested improvements are realistic and closely linked to the problems they identified.
- The student shows awareness that better temperature control and improved data resolution would strengthen the investigation.
- The student's evaluation demonstrates that they are thinking critically about how the method affected the results.
- The student does not fully explain which limitation had the largest impact on the results.
- Some weaknesses are identified clearly, but their relative effect on the final discrepancy is not analysed in enough depth.
- One improvement would be stronger if it were made independent of the theory being tested.
- The student could be more explicit about how each improvement would change the data or reduce error.
- The scientific implication of finer concentration spacing could be developed further.
4.1·Weakness
Page 18
The limitation is relevant, but the evaluation should explain how much this assumption likely affected the results. Without linking it to the size of the 13.5–23.9% discrepancies, the student cannot show which weakness had the greatest impact.
4.2·Strength
Page 18
The student identifies a specific methodological limitation and explains why it matters to the validity of the calorimetry model. This is strong evaluation because it moves beyond naming a weakness and connects the assumption directly to the measured values.
4.3·Suggestion
Page 18
This improvement is realistic and relevant. It would be even stronger if the student explained how insulation would specifically change the calculated or reduce systematic underestimation of the specific heat capacity.
4.4·Question
Page 19
How would smaller concentration increments change the interpretation of the trend, especially around the mid-range where the decline appears less uniform? Reflecting on that would help the student justify why this improvement matters scientifically.
4.5·Suggestion
Page 19
The student has identified a sensible direction for improvement, but the method would be stronger if the calibration were independent of the theoretical values being tested. Consider instead measuring electrical input directly and correcting for heat loss from the temperature-time curve.