IM

EESIA Rubric Breakdown

Identification

  • This is the first criterion, with a word count limit of 400 words. It encompasses the initial framing of your research, including the chosen topic and formulated research question.

Methodology and Planning (6 Marks)

  • Sufficient Data Collection:

    • Your methodology must ensure the collection of sufficient and comprehensive data.

    • For surveys, this means distributing them to an adequate number of people.

    • For soil sampling, this involves taking samples from diverse areas to gather a comprehensive dataset.

    • Appropriate sampling methods, such as random sampling, transect sampling, or snowball sampling, must be employed.

    • If using secondary data, ensure sufficient secondary data sampling.

    • The volume of data collected is crucial because subsequent statistical analyses (e.g., Chi-square, T-test) require a series of data points.

  • Sampling Strategy Justification:

    • You must justify the specific method and locations chosen for sampling your data.

    • Site Selection: If collecting soil samples from a protected forest (e.g., 5 different areas), clearly justify why those particular sites were selected. Provide a map clearly denoting the sampling locations.

    • Specific Choices: If surveying in field work involving plant manipulation (e.g., growth, germination), justify the choice of specific plants (e.g., a plant that grows better or yields data faster).

    • Independent Variable Range: Justify the range of your independent variable (e.g., if germinating seeds for 10, 15, or 30 days, explain the rationale behind these durations).

    • Repeats: Justify the number of repeats performed (e.g., if using 5 replicates of seeds with different concentrations in a Petri dish, explain why 5 repeats were chosen).

    • Measurement Increments: If measuring pollution at specific distances (e.g., 5 meters, 10 meters, 15 meters) from a road into a forest, justify these specific increments.

    • Control Variables: Justify all control variables established in your experiment.

  • Risk Assessment:

    • Identify all potential hazards and risks involved in your research.

    • Detail how these hazards and risks will be mitigated or overcome.

    • Physical Risks: Examples include falling, cuts, or slipping during physical fieldwork.

    • Laboratory Risks: Consider potential contamination with bacteria or adherence to animal experimentation policies.

    • Ethical Risks:

      • Environmental Impact: Ensure that data collection (e.g., soil samples from the physical environment) is done ethically, causing no damage, and that the environment is left in its original state.

      • Waste Disposal: Ensure proper and careful disposal of any waste generated.

      • Surveys: Obtain necessary permissions, use clear and easily understandable language, and protect participant privacy by not forcing answers to sensitive questions. All survey methods should be clearly written and numbered.

Results, Analysis, and Conclusion

  • Presenting Raw Data:

    • Present your raw data in a clear, concise, and well-organized manner.

    • Tables should be clearly labeled, include appropriate headings, and state uncertainties and the least count of instruments used.

    • Uncertainties must be presented in suitable places throughout the data.

  • Data Processing and Analysis:

    • Processed data should also be clearly labeled.

    • Include averages, standard deviation, and other relevant statistical tests (e.g., Chi-square, T-test).

    • Statistical tests are crucial for reducing subjectivity in the ESI, making the results more objective and providing a valid justification for findings.

    • Ensure all tables and graphs have clear titles.

    • Provide a worked example demonstrating the calculation of averages and standard deviation.

    • Construct appropriate graphs for your data:

      • Understand which graph type (e.g., pie chart, scatter plot, bar graph) is suitable for each kind of data.

      • For example, a Pearson's correlation coefficient should ideally be represented by a straight line, not a curve.

      • If calculated, standard deviation should be presented on the graph (e.g., as error bars).

      • Axes on graphs must be clearly labeled.

      • Plot averages on graphs where applicable.

      • Identify and discuss any anomalies in your data.

      • Discuss the overlap or non-overlap of error bars to evaluate the reliability of your data.

  • Conclusion:

    • Your conclusion must directly answer your research question.

    • Explain the significance of any calculated averages and standard deviations.

    • Ensure your conclusion is consistent with and supported by the data you have presented.

    • Clearly explain any trends or patterns observed in your data.

Discussion and Evaluation

  • Discussion:

    • Link your findings to the environmental issue and research question initially identified.

    • Discuss how your results are relevant to the broader environmental issue.

    • Explain how your results enhance understanding of the impacts of the environmental issue.

    • Connect your results to other studies, either confirming or contradicting previous research.

  • Evaluation:

    • Evaluation of Conclusion: Assess the strengths of your conclusion.

    • Evaluation of Method:

      • Discuss the strengths of your methodology.

      • Discuss the weaknesses of your methodology.

      • Propose concrete improvements for at least one of the identified weaknesses. These modifications should aim to enhance the reliability of the method.

  • Areas for Further Study:

    • Discuss potential areas for further study.

    • These areas should be sharply focused and clearly defined, avoiding vague or tenuous links.

    • Discuss the ramifications or potential outcomes if these areas of further study were to be implemented.

Application (3 Marks)

  • Specific Application/Further Study:

    • Propose one particular application or area for further study that is closely linked to your research question.

  • Justification:

    • Justify your choice of this specific solution or further research direction.

    • A useful hint is to try and find a case study where such an application is already in action or being considered.

    • If your study leads to a new thought or idea, discuss its potential for future implementation and its benefits.

  • Strengths & Weaknesses:

    • State at least two (ideally three) good strengths of your proposed application or solution.

    • Clearly state the weaknesses and limitations of the application. Ensure to distinguish between weaknesses and limitations.

Communication (3 Marks)

  • Word Count:

    • The maximum word count for the ESI is 2250 words.

    • The following items are not included in the word count:

      • Acknowledgments

      • Contents page

      • Title

      • Subtitles

      • Cited footnotes

      • Photographs

      • Maps

      • Legends

      • Labels

      • Tables of statistical or numerical data (including categories, classes, or groups)

      • Names

      • Bibliography

  • Overall Structure and Weighting:

    • Key sections for scoring maximum marks include Identification (Context), Planning, Results Analysis & Discussion, Application, and Communication.

    • The total marks for the ESI are 30.

    • Planning accounts for 6 marks, Application for 3 marks, and Communication for 3 marks.