Biology IA Exemplar: What is the effect of different concentrations… | RevisionDojo

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IB Biology HL Internal Assessment Example

What is the effect of different concentrations of ammonium chloride (0.00 M control , 0.10 M, 0.20 M,0.30 M, 0.40 M, and 0.50 M ± 0.01 mol dm-3) on the average daily stem growth rate (cm day-1±0.1 cm ) of Phaseolus vulgaris seedlings over an 8-day period (Days 4-11 post planting )?HL

Official IB Result

18/24

Criteria A: Research Design

6/6

Criteria StrandsPro

A.1Research question context

Excellent

A.2Methodological considerations

Good

A.3Methodology description

Good

Criteria Feedback

The student framed a focused, specific research question that clearly identifies the organism, variable, treatments, and measurement window.
The student justified the investigation with relevant biological context about ammonium stress and seedling growth.
The student showed thoughtful planning by using a pilot study to refine the concentration range and procedure.
The student included several important controls and methodological features such as replication, random allocation, and standardized growth conditions.

Some methodological choices are described but not fully explained in terms of why they were needed for valid and sufficient data.
The added distilled water creates a confounding factor because it changes moisture conditions and may alter the effective concentration.
A few procedural details are still ambiguous, so another researcher could repeat the investigation only with some uncertainty.

1.1·Strength

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The research question is impressively specific: it identifies the species, six treatment levels, the dependent variable with units, and the measurement window. That level of focus makes the investigation feasible and gives the reader a clear sense of exactly what was tested.

1.2·Strength

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This background successfully justifies why stem height is a suitable dependent variable for this species. The student connects the biology of ammonium stress to a measurable trait, which strengthens the rationale for the design rather than presenting the topic in isolation.

1.3·Weakness

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The method for preparing solutions is partly clear, but the wording is too imprecise to be fully reproducible. The student should state the exact calculation method, whether masses were measured separately for each concentration, and how the final volume was made up in the flask so another researcher could repeat it without ambiguity.

1.4·Strength

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The student has identified a genuinely important confounding variable rather than ignoring it. Naming the extra distilled-water volume shows awareness that moisture conditions can affect growth and treatment strength, which is exactly the kind of control consideration expected at HL.

1.5·Weakness

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This control weakens the design because the extra water is variable and not operationally defined. The student should explain how the added water amount was decided for each pot, or better, standardize soil moisture across all treatments; otherwise, moisture becomes a confounder that affects both growth and the effective NH4Cl concentration.

1.6·Suggestion

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A short note explaining how the same person measured every plant, or how inter-observer variation was prevented, would strengthen reproducibility. Even a well-chosen instrument can produce inconsistent data if the measurement protocol is not standardised across days.

1.7·Weakness

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Random allocation is a good start, but the method is incomplete because it does not explain how randomisation was carried out. The student should specify the random method used and whether pots were repositioned during the experiment, since bench location can create systematic light or temperature differences.

1.8·Strength

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The pilot study is a major strength because the student shows how it directly informed design decisions. Explaining the changes from the preliminary trial makes the investigation more purposeful and demonstrates methodological reflection rather than simply mentioning a pilot.

1.9·Question

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What specific evidence from the pilot showed that 3 cm planting depth caused the control to emerge too slowly? If the student can link the pilot observation more explicitly to the later design change, the rationale for lowering the depth will be much stronger.

Criteria B: Data Analysis

4/6

Criteria StrandsPro

B.1Communication of data recording and processing

Moderate

B.2Consideration of uncertainties

Moderate

B.3Data processing quality

Poor

Criteria Feedback

The student presents a substantial amount of relevant raw and processed data using tables, graphs, and observational notes.
The student's figures and tables generally identify variables, units, and sample sizes clearly enough to follow the investigation.
The student makes a real attempt to quantify variation by including standard deviations and error bars.
The student identifies a clear overall trend in growth as treatment concentration increases.

Several numerical and labeling inconsistencies make parts of the processing hard to verify.
Some calculations do not match the raw values or the stated time interval, which weakens confidence in the derived results.
The student's treatment of uncertainty is present, but it does not fully separate random variation from systematic error.
The statistical handling raises an independence concern because repeated measurements from the same plants appear to be treated as separate observations.

2.1·Strength

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The raw-data table is well labelled and gives enough context to understand what was measured, when it was measured, and how many replicates were used. That makes the data easier to follow and supports traceability from raw values to processed results.

2.2·Weakness

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This sentence conflicts with the surrounding table and creates uncertainty about where the full dataset is actually located. The student should correct the day reference and ensure that table numbering and appendix references are consistent throughout the report.

2.3·Weakness

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The worked mean example is useful, but it should match the displayed raw values exactly and show the arithmetic more clearly. At the moment, the calculation is difficult to verify because the notation is cluttered and the link between the sum and the reported mean is not transparent.

2.4·Strength

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The processed table is used effectively here to identify the main trend in the dataset. This is a strong example of turning numerical results into an interpretable pattern rather than listing values without synthesis.

2.5·Weakness

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The percentage-change method is mathematically clear in principle, but the worked example later appears inconsistent with the values shown. The student should check that every derived value matches the raw data and that the formula is applied using the correct heights and time interval.

2.6·Weakness

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This table entry appears to be missing the separator between the mean and standard deviation, which makes the processed value hard to read. The student should format each result consistently as mean

\pm

SD so the data can be checked and compared quickly.

2.7·Weakness

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This interpretation overstates what standard deviation can show. Low spread among replicates suggests consistency, but it does not prove accuracy or eliminate systematic error. The student should distinguish between random variation and measurement validity, especially because other confounders remain unmeasured.

2.8·Weakness

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The figure caption communicates the graph’s purpose well, but the uncertainty notation needs correction because the standard deviation symbol is not clearly rendered. The student should ensure the figure legend uses unambiguous notation so the reader can interpret the error bars without guessing.

2.9·Weakness

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This processing choice raises a serious independence issue. Repeated daily increments from the same plants are not independent observations, so treating all 35 increments per treatment as separate data points inflates sample size and can distort the box plot and any inferential statistics based on it.

2.10·Question

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How were the degrees of freedom obtained, and what exactly was entered as the independent observations for the ANOVA? If daily increments from the same plant were pooled, the test may not meet the independence assumption required for a valid result.

2.11·Weakness

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This claim is too sweeping for the evidence shown. The student should avoid saying that NH4Cl in any treatment was significant in stopping growth when the comparison with 0.10 M is described more cautiously. The conclusion must match the pairwise results exactly.

Criteria C: Conclusion

6/6

Criteria StrandsPro

C.1Conclusion relevance and consistency

Moderate

C.2Scientific context comparison

Moderate

Criteria Feedback

The student answers the research question directly and keeps the conclusion focused on the main growth trend.
The student's overall conclusion matches the broad pattern seen in the processed data and observations.
The student makes relevant links to accepted biological mechanisms such as ammonium toxicity and osmotic stress.
The student uses scientific context to help explain why the observed pattern may have occurred.

The student's conclusion becomes more definite than the supporting analysis allows, especially where calculation inconsistencies remain unresolved.
The exact threshold or magnitude of effect is not securely established from the evidence presented.
Some comparisons with external scientific studies are relevant but too loosely matched to support stronger species-level claims.
The conclusion would be stronger if it acknowledged the limits created by concentration drift and other confounding factors.

3.1·Strength

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The conclusion directly answers the research question and matches the overall pattern in the processed data. This is effective because it states the central finding without drifting into unrelated detail.

3.2·Weakness

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The conclusion overstates precision because the analysis contains unresolved inconsistencies in the time interval and derived growth-rate calculations. The student should keep the conclusion tied to what can be supported confidently by the processed data rather than implying a more exact numerical basis than the investigation actually demonstrates.

3.3·Suggestion

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It would be stronger to qualify this claim with the experimental limitations that affect the exact threshold, especially the changing water additions and likely concentration drift. That would make the conclusion more accurate without weakening the overall trend the student identified.

3.4·Strength

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The student strengthens the conclusion by connecting the observed trend to accepted biological mechanisms. That comparison works well because it shows understanding of why the pattern occurs rather than simply restating the graph.

3.5·Weakness

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This comparison goes beyond what the investigation can firmly establish. The student would need closely matched evidence and a stronger species comparison before claiming beans are relatively sensitive; otherwise, the statement should be framed more tentatively as a possible interpretation rather than a conclusion.

Criteria D: Evaluation

2/6

Criteria StrandsPro

D.1Methodological weaknesses

Excellent

D.2Improvements

Poor

Criteria Feedback

The student identifies several concrete limitations rather than relying on generic comments.
The student shows awareness that multiple mechanisms could explain the observed growth reduction.
The student discusses important weaknesses such as changing concentration, pH effects, osmotic stress, and the narrowness of shoot height as a response variable.
The student recognizes that the short duration and measurement issues affect how confidently the results can be interpreted.

The student's explanation of which limitations matter most is present but not consistently developed in detail.
The suggested improvements are limited and do not always directly target the weaknesses the student identified.
Some comments on error and uncertainty are too dismissive of systematic issues.
A more effective evaluation would clearly connect each weakness to a practical, specific change in method.

4.1·Weakness

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This strength statement is too general because it does not distinguish which controls were most effective or which limitations remained. The student should explain the relative importance of the controls and connect them to the specific weaknesses discussed later in the evaluation.

4.2·Strength

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The limitation is well chosen because it targets the dependent variable itself. Explaining that shoot height alone may miss root damage shows deeper methodological understanding and connects directly to how the data were collected.

4.3·Question

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If root effects are central to ammonium stress, what measurement would better capture the plant’s response: root length, root mass, or a root:shoot ratio? Thinking about the dependent variable in this way would help the student design a more complete follow-up investigation.

4.4·Weakness

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This conclusion about error significance is too dismissive. Low standard deviations do not show that timing or measurement error is negligible, especially when the dependent variable is a daily growth rate. The student should explain which errors are likely random, which are systematic, and how each would influence the results.

4.5·Strength

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This is a sophisticated limitation because it shows awareness that more than one mechanism could explain the effect. The student is not just listing weaknesses; they are analysing why the design cannot isolate the cause of the growth reduction.

4.6·Strength

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The student identifies a specific limitation and explains its effect on the validity of the results. This is strong evaluation because it links a concrete procedural issue to a plausible distortion of the final trend.

4.7·Suggestion

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To address this limitation, the student could compare NH4Cl with an iso-osmotic non-ionic solute control. That would help separate osmotic effects from ion-specific toxicity and would make the evaluation much more directly tied to the weakness identified.

4.8·Strength

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The student assesses the timeframe thoughtfully rather than simply saying it was “too short.” This works well because it explains the specific consequence of the limited duration on the reliability of the interpretation.

4.9·Suggestion

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A practical improvement would be to measure soil pH at set intervals and compare it with a control buffer or pH-adjusted treatment. That would directly test whether acidity, rather than ammonium concentration alone, contributed to the reduced growth.

4.10·Suggestion

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This is an interesting extension, but it would be even stronger if it were linked to a concrete improvement in the original design. For example, the student could explain how microbial measurements would complement the current findings and help distinguish plant toxicity from broader soil effects.

Loading scores...

Official IB Result

18/24

Criteria A: Research Design

6/6

Criteria StrandsPro

A.1Research question context

Excellent

A.2Methodological considerations

Good

A.3Methodology description

Good

Criteria Feedback

The student framed a focused, specific research question that clearly identifies the organism, variable, treatments, and measurement window.
The student justified the investigation with relevant biological context about ammonium stress and seedling growth.
The student showed thoughtful planning by using a pilot study to refine the concentration range and procedure.
The student included several important controls and methodological features such as replication, random allocation, and standardized growth conditions.

Some methodological choices are described but not fully explained in terms of why they were needed for valid and sufficient data.
The added distilled water creates a confounding factor because it changes moisture conditions and may alter the effective concentration.
A few procedural details are still ambiguous, so another researcher could repeat the investigation only with some uncertainty.

1.1·Strength

Page 1• Click to view

1.2·Strength

Page 3• Click to view

1.3·Weakness

Page 4• Click to view

1.4·Strength

Page 5• Click to view

1.5·Weakness

Page 6• Click to view

1.6·Suggestion

Page 6• Click to view

1.7·Weakness

Page 6• Click to view

1.8·Strength

Page 7• Click to view

1.9·Question

Page 7• Click to view

Criteria B: Data Analysis

4/6

Criteria StrandsPro

B.1Communication of data recording and processing

Moderate

B.2Consideration of uncertainties

Moderate

B.3Data processing quality

Poor

Criteria Feedback

The student presents a substantial amount of relevant raw and processed data using tables, graphs, and observational notes.
The student's figures and tables generally identify variables, units, and sample sizes clearly enough to follow the investigation.
The student makes a real attempt to quantify variation by including standard deviations and error bars.
The student identifies a clear overall trend in growth as treatment concentration increases.

Several numerical and labeling inconsistencies make parts of the processing hard to verify.
Some calculations do not match the raw values or the stated time interval, which weakens confidence in the derived results.
The student's treatment of uncertainty is present, but it does not fully separate random variation from systematic error.
The statistical handling raises an independence concern because repeated measurements from the same plants appear to be treated as separate observations.

2.1·Strength

Page 8• Click to view

2.2·Weakness

Page 8• Click to view

2.3·Weakness

Page 9• Click to view

2.4·Strength

Page 10• Click to view

2.5·Weakness

Page 10• Click to view

2.6·Weakness

Page 10• Click to view

This table entry appears to be missing the separator between the mean and standard deviation, which makes the processed value hard to read. The student should format each result consistently as mean

\pm

SD so the data can be checked and compared quickly.

2.7·Weakness

Page 10• Click to view

2.8·Weakness

Page 11• Click to view

2.9·Weakness

Page 13• Click to view

2.10·Question

Page 14• Click to view

2.11·Weakness

Page 15• Click to view

Criteria C: Conclusion

6/6

Criteria StrandsPro

C.1Conclusion relevance and consistency

Moderate

C.2Scientific context comparison

Moderate

Criteria Feedback

The student answers the research question directly and keeps the conclusion focused on the main growth trend.
The student's overall conclusion matches the broad pattern seen in the processed data and observations.
The student makes relevant links to accepted biological mechanisms such as ammonium toxicity and osmotic stress.
The student uses scientific context to help explain why the observed pattern may have occurred.

The student's conclusion becomes more definite than the supporting analysis allows, especially where calculation inconsistencies remain unresolved.
The exact threshold or magnitude of effect is not securely established from the evidence presented.
Some comparisons with external scientific studies are relevant but too loosely matched to support stronger species-level claims.
The conclusion would be stronger if it acknowledged the limits created by concentration drift and other confounding factors.

3.1·Strength

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3.2·Weakness

Page 15• Click to view

3.3·Suggestion

Page 15• Click to view

3.4·Strength

Page 15• Click to view

3.5·Weakness

Page 16• Click to view

Criteria D: Evaluation

2/6

Criteria StrandsPro

D.1Methodological weaknesses

Excellent

D.2Improvements

Poor

Criteria Feedback

The student identifies several concrete limitations rather than relying on generic comments.
The student shows awareness that multiple mechanisms could explain the observed growth reduction.
The student discusses important weaknesses such as changing concentration, pH effects, osmotic stress, and the narrowness of shoot height as a response variable.
The student recognizes that the short duration and measurement issues affect how confidently the results can be interpreted.

The student's explanation of which limitations matter most is present but not consistently developed in detail.
The suggested improvements are limited and do not always directly target the weaknesses the student identified.
Some comments on error and uncertainty are too dismissive of systematic issues.
A more effective evaluation would clearly connect each weakness to a practical, specific change in method.

4.1·Weakness

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4.2·Strength

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4.3·Question

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4.4·Weakness

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4.5·Strength

Page 17• Click to view

4.6·Strength

Page 17• Click to view

4.7·Suggestion

Page 17• Click to view

4.8·Strength

Page 17• Click to view

4.9·Suggestion

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4.10·Suggestion

Page 17• Click to view