IB Environmental systems and societies (ESS) - Old SL Internal Assessment Example

The research question is clear and focused but lacks operational definitions for "extent" and quantifiable awareness criteria. Defining measurable indicators would enhance precision and alignment with the investigable scope.

Background section provides relevant e-commerce and plastic life-cycle data, but the COD trend is described without context or units. Explain the significance of COD values and axes for reader clarity.

The map of the study area effectively situates Klang Valley, strengthening context. Consider adding a scale bar and data source citation directly on the map for completeness.

Variables table is comprehensive but the concept of “awareness” should be operationalized. Add a definition of awareness levels linked to specific survey items to justify method design.

Ethical considerations are outlined, but a formal risk matrix is absent. Create a succinct risk assessment table detailing potential online privacy, data breach, and mitigation strategies.

The sampling justification cites the Central Limit Theorem but does not explain how age strata were selected. Include rationale for age-group thresholds, sampling quotas, and representativeness justification.

Convenience sampling via a single WhatsApp group introduces bias and limits representativeness. Justify why this strategy can yield a balanced sample or consider stratified recruitment across different community forums.

Table 4 lists all questions and justifications, which is thorough. However, some justification cells are blank. Ensure each survey item has a clear justification linked to knowledge, attitudes, or practice goals.

Figure 1 is informative but lacks clear axis labels and units for COD. Ensure each chart includes labeled axes, units, and a brief description of data sources to improve data presentation.

Raw data tables are comprehensive but overcrowded and contain illegible symbols. Simplify presentation by removing OCR artifacts and summarizing key statistics instead of full raw data.

The percentage calculation formula is shown clearly, but the narrative should interpret what 26.67% implies for question A3. Link the example to broader data patterns.

Table 9 is dense and difficult to follow due to merged cells and symbols. Simplify by splitting into separate tables for each age group or key question to enhance clarity.

Figure 4 interpretation effectively links generational differences to cost concerns. Consider adding numerical values on the chart bars to reinforce comparisons for each age group.

Figure 3’s caption and discussion restate percentages but the figure axes and legend are not referenced. Cite axis labels in the analysis and discuss data limitations due to sampling imbalance.

Table 10 effectively summarizes means, SDs, and p-values, but decimal places vary inconsistently. Standardize to two decimal places across all cells.

Analysis of Figure 6 correctly identifies outliers and SD trends. To deepen evaluation, discuss effect sizes or confidence intervals to quantify the magnitude of differences.

Analysis text overstates causality between awareness and age. Clarify that correlations do not imply causation and acknowledge potential confounding variables.

Conclusion reiterates the hypothesis support but overgeneralizes from neutral mean differences. Instead, discuss the limited effect sizes and acknowledge when differences fall below practical significance.

Figure 7 illustrates practice patterns well but the p-value discussion is confusing—practices were described as non‐significant yet previous results had significant p-values. Reconcile these findings.

Discussion uses relevant secondary literature to contextualize conclusions. Strengthen DEV by integrating this literature to critically evaluate anomalies and compare effect sizes.

Improvement suggestions are meaningful—multi-platform distribution and open-ended items. For greater depth, propose specific sample-size calculations and targeted demographic quotas.

The evaluation rightfully flags cultural and education biases but lacks quantitative assessment of sampling error. Include a discussion of confidence intervals or margin of error to evaluate reliability.

Application proposal suggests a culturally tailored campaign. To justify feasibility, include resource estimates, stakeholder analysis, and monitoring metrics to evaluate effectiveness.

Overall report structure follows IB conventions but lengthy raw-data appendices disrupt flow. Consider moving exhaustive data tables to an appendix and summarizing key findings in the main text for improved logic.

Mean and SD equations are properly formatted in LaTeX. Including an interpretation sentence directly after each calculation would reinforce the statistical reasoning.

References list is extensive but inconsistent formatting and missing DOIs hinder credibility. Apply a single citation style (APA/Chicago) and ensure complete entries.