Class | Mark | Marking Guidelines |
Distinction | | The research question is framed clearly and insightfully in relation to the scenario.
Relevant Open Play data are selected, linked, and prepared with a very high level of competence, with methodological decisions exceptionally well justified.
Feature engineering is thoughtful, relevant to the question, and clearly explained.
The analytical strategy is highly appropriate to the dataset and research question, with strong justification for modelling choices.
Model evaluation is very strong, with careful attention to assumptions, diagnostics, robustness, and limitations.
Results are communicated very clearly, accurately interpreted, and integrated into a coherent overall conclusion.
There is strong evidence of critical reflection throughout, including awareness of bias, uncertainty, and the limits of inference.
|
Excellent Distinction | 100 | Assignment reaches an exceptional level of achievement that significantly exceeds the standards described by the above statements |
Good Distinction | 90 | Assignment exceeds the standards described by the above statements |
Solid Distinction | 80 | Assignment is well described by the above statements |
Low Distinction | 75 | Assignment mostly meets the standards described by the above statements |
Merit | | The research question is framed clearly in relation to the scenario.
Relevant Open Play data are selected and prepared appropriately.
Feature engineering is generally appropriate and relevant.
The analytical strategy is generally suitable.
Appropriate assumptions, diagnostics, and/or robustness checks are considered.
Results are described clearly.
There is good evidence of critical reflection.
|
Good Merit | 68 | Assignment exceeds the standards described by the above statements but does not meet the standards for a Distinction |
Solid Merit | 65 | Assignment is well described by the above statements |
Low Merit | 62 | Assignment mostly meets the standards described by the above statements |
Pass | | The research question is framed in relation to the scenario, although some elements of rationale may be underdeveloped.
The relevant Open Play data are selected and prepared, however, some decisions may be suboptimal or not fully justified.
The feature engineering is generally appropriate and relevant, but some features may be limited in ambition, clarity, or justification.
The analytical strategy is generally suitable, aspects of model choice or implementation appear to lack full justification or contain a number of weaknesses.
The assumptions, diagnostics, and/or robustness checks are considered and typically appropriate, however, the evaluation is not fully developed.
The results are described, although some minor errors or simplifications in interpretation may be present.
Some evidence of critical reflection, although it may be uneven or limited in depth.
|
Good Pass | 58 | Assignment exceeds the standards described by the above statements but does not meet the standards for a Merit |
Solid Pass | 55 | Assignment is well described by the above statements |
Low Pass | 52 | Assignment mostly meets the standards described by the above statements |
Marginal Fail | | The methodological approach is only superficially described or justified in relation to the dataset and question.
Relevant data are typically selected, but there may be weaknesses in linkage, preparation, or explanation.
Feature engineering appears limited, under-justified, or only partly aligned with the research question.
The analytical model is only partially related to the data structure and research question and may contains one or more errors, omissions, or poorly justified choices in core components.
There is partial consideration of assumptions, diagnostics, or robustness, but this may be very limited in depth or accuracy.
Results are reported, but interpretation contains errors, oversimplifications, or weak links to the original question.
There is limited evidence of critical reflection on bias, limitations, or uncertainty.
|
Good Marginal Fail | 48 | Assignment exceeds the standards described by the above statements but does not meet the standards for a Pass |
Solid Marginal Fail | 45 | Assignment is well described by the above statements |
Low Marginal Fail | 42 | Assignment falls below the standards described by the above statements |
Fail | | The methodological approach is weakly structured, weakly justified, or only partly relevant to the research question.
There are significant weaknesses in data selection, linkage, and preparation.
Feature construction is poorly executed.
The analytical model contains substantial errors or is poorly matched to the data structure and research question.
There is little or no meaningful consideration of assumptions, diagnostics, or robustness.
There are significant errors in reporting or interpreting the results.
Critical reflection is missing or weak, especially in relation to bias, uncertainty, and limitations.
|
High Fail | 38 | Assignment exceeds the standards described by the above statements but does not meet the standards for a Pass |
Low Fail | 32 | Assignment is well described by the above statements |
Outright Fail | 10 | Assignment falls below the standards described by the above statements |
Zero Marks | 0 | No relevant content |