Environmental systems and societies (ESS) - Old IA Exemplar:… | RevisionDojo
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IB Environmental systems and societies (ESS) - Old SL Internal Assessment Example
To what extent does household income level influence differences in electricity consumption behaviors in Surabaya, Indonesia?SL
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5
Official IB Result
18/30
Criteria A: Identifying the Context (CXT)
5/6
0
3
6
Criteria Strands
A.1Research question formulation
Excellent
A.2Environmental issue context
Excellent
A.3Connection between issue and research
Good
Criteria Feedback
Clear, coherent and focused research question directly linked to variables
Sustained discussion of global and local context narrowing to Surabaya’s electricity demand
Well-explained connection between income disparities and conservation policy
Minor wording redundancy in research question reduces precision
Context section drifts into generic climate facts rather than Surabaya-specific data
Connections to economic, social, and technological factors are described superficially
1.1·Suggestion
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Minor wording redundancy in “influence differences” reduces precision; consider rephrasing the research question to avoid duplication of terms.
1.2·Suggestion
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Link between the issue and research question would be stronger with local statistics on household consumption to support claims about Surabaya.
1.3·Weakness
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The environmental context is thorough but drifts into generic climate facts; tighten focus by incorporating Surabaya-specific emissions or electricity data.
1.4·Weakness
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Economic, social, and technological factors are mentioned superficially; deepen the connection with specific policy or demographic evidence for Surabaya.
Criteria B: Planning (PLA)
3/6
0
3
6
Criteria Strands
B.1Method design
Good
B.2Sampling strategy
Poor
B.3Risk and ethical considerations
Moderate
Criteria Feedback
Method design is repeatable and appropriate (Google Form → ANOVA)
Ethical considerations of consent and anonymity are outlined
Hypotheses and variable classification are clearly stated
Sampling strategy is un-justified convenience sampling with potential bias
Procedure omits data-cleaning protocol and handling of missing responses
Risk assessment is brief, lacking data-security measures and IRB approval details
2.1·Suggestion
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The final sentence on survey scope is cut off; complete the thought and clarify how the design addresses the research aims.
2.2·Suggestion
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Hypotheses are stated clearly, but adding anticipated directionality (e.g., “higher income → lower consumption score”) would enhance specificity.
2.3·Suggestion
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Variable classification is comprehensive; strengthen by specifying planned sample sizes per income group to justify the five categories.
2.4·Weakness
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Procedure is replicable but omits guidelines for managing missing or partial survey responses; include a data-cleaning protocol.
2.5·Suggestion
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Sampling via friends and teachers introduces bias; justify this convenience approach or propose stratification to improve representativeness.
2.6·Suggestion
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The Likert scale is appropriate for frequency measures; consider pilot testing to ensure items function equivalently across income groups.
2.7·Suggestion
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Justification of one-way ANOVA is sound; add explicit mention of assumption checks (normality, homogeneity of variance) before analysis.
2.8·Weakness
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Environmental risks and data security are under-addressed; elaborate on measures for protecting respondents’ digital data and privacy.
2.9·Suggestion
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Ethical evaluation notes privacy but omit whether IRB or institutional review approval was obtained; clarify research oversight.
Criteria C: Results, Analysis and Conclusion (RAC)
3/6
0
3
6
Criteria Strands
C.1Data presentation
Moderate
C.2Data analysis
Moderate
C.3Conclusion drawing
Moderate
Criteria Feedback
Appropriate choice of bar charts and Tukey HSD to display group differences
Correct application of ANOVA and interpretation of p-values
Conclusion relates observed trends to behavioural explanations
Multiple tables are malformed or contain placeholder text
Not all survey questions are fully presented; summary statistics are missing
No effect-size reporting or assumption checks documented
3.1·Suggestion
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Referencing processed data is helpful, but summary statistics (means, SDs) should be displayed immediately to guide reader understanding.
3.2·Suggestion
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Interpretation of p > 0.05 is correct; consider reporting effect size (e.g., η2) to convey the magnitude of non-significance.
3.3·Weakness
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ANOVA table for Question 1 is malformed and contains placeholder text; reconstruct output to show actual F- and p-values clearly.
3.4·Suggestion
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The Tukey HSD figure is useful; ensure axes, group labels, and confidence intervals are legible and annotated for clarity.
3.5·Weakness
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ANOVA output for Question 4 contains nonsensical symbols; rerun analysis and ensure software export displays numeric results correctly.
3.6·Weakness
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ANOVA table for Question 6 is illegible; replace placeholder symbols with actual F- and p-values to support the conclusion.
3.7·Suggestion
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Group-level null results are clear; consider summarizing non-significant outcomes in a consolidated table to streamline reading.
Criteria D: Discussion and Evaluation (DEV)
3/6
0
3
6
Criteria Strands
D.1Conclusion evaluation
Moderate
D.2Method evaluation
Moderate
D.3Improvements and extensions
Moderate
Criteria Feedback
Evaluation links statistical outcomes to mitigation and policy implications
Method strengths and weaknesses are identified (repeatability, bias, scale issues)
Improvements proposed are meaningful (meter data, equal sample sizes)
Evaluation lacks external literature or policy trade-off discussion
Limitations are listed rather than critically analysed (e.g., confounding variables)
Suggested improvements are relevant but not sufficient to address major weaknesses fully
4.1·Suggestion
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Controlled variables ensure consistency, but limiting age to 25–40 may reduce generalizability; discuss this trade-off in the evaluation section.
4.2·Suggestion
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After rejecting H₀ for high-energy appliances, briefly discuss potential policy actions tailored to Surabaya households for this behaviour.
4.3·Suggestion
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Conclusion restates key findings but would benefit from comparing results with literature to provide broader theoretical context.
4.4·Suggestion
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Limitations table notes focus on income; include discussion of unequal group sizes’ effect on ANOVA validity to fully evaluate method.
4.5·Suggestion
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Proposed inclusion of actual electricity usage is strong; extend suggestion by outlining mixed-methods integration of meter data with self-reports.
Criteria E: Applications (APP)
2/3
0
2
3
Criteria Strands
E.1Application proposal
Excellent
E.2Solution evaluation
Good
Criteria Feedback
Application proposal is clearly justified using study findings
Consideration of emissions impact and subsidy rationale is explicit
Evaluation of solution omits key factors (rebound effects, monitoring strategies)
Discussion of weaknesses is partial and lacks broader socio-economic considerations
5.1·Suggestion
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Application proposal is well tied to findings; further evaluate potential rebound effects and outline monitoring strategies for subsidy success.
5.2·Suggestion
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Good use of pre-paid meter system literature; ensure consistent citation formatting and include more local policy examples for depth.