Module Rubric

This rubric is used to assess each module at graded checkpoints (after modules 1, 3, 5, and 7).

Criteria

Does the module work as specified?

Points	Description
8	All features work correctly. Handles edge cases gracefully. No crashes or unexpected behavior.
6	Core features work correctly. Minor edge cases may be unhandled. Rare minor bugs.
4	Main functionality works but with notable bugs or missing features.
2	Partially functional. Major features broken or incomplete.
0	Non-functional or not submitted.

Is the code clean, readable, and well-structured? See the Code Elegance Rubric for detailed criteria.

Points	Description
8	Exemplary code quality. Clear structure, excellent naming, appropriate abstraction.
6	Good code quality. Readable and organized with minor issues.
4	Acceptable code quality. Functional but messy, inconsistent, or poorly organized.
2	Poor code quality. Difficult to read, understand, or maintain.
0	Unacceptable. Incomprehensible or no meaningful code submitted.

Are unit tests and integration tests present, meaningful, and passing?

Points	Description
8	Comprehensive test coverage. Tests are well-designed, test meaningful behavior, and all pass. Edge cases covered.
6	Good test coverage. Most important functionality tested. Tests pass. Minor gaps in coverage.
4	Basic test coverage. Some tests present but incomplete or superficial. Tests may not cover key functionality.
2	Minimal testing. Few tests, poorly written, or significant failures.
0	No tests or tests completely non-functional.

Do commit histories show meaningful contribution from all team members?

Points	Description
6	All team members show substantial, balanced contributions. Commits reflect genuine work, not artificial splitting.
4	All team members contributed. Some imbalance but all participated meaningfully.
2	Participation imbalance is notable. One member dominates or one member's contributions are minimal.
1	Severe imbalance. One or more members show little evidence of contribution.
0	No evidence of team collaboration. Single contributor or no commits.

Is the code documented according to standard Python practices?

Points	Description
5	Excellent documentation. All public functions have docstrings with parameter and return descriptions. Type hints used consistently. Complex logic has inline comments. README explains module usage.
4	Good documentation. Most functions documented. Type hints present. Minor gaps.
3	Basic documentation. Some docstrings present but inconsistent or incomplete.
1	Minimal documentation. Little to no docstrings. Code is difficult to understand without reading implementation.
0	No documentation.

Are inputs and outputs clearly defined and easily assessable?

Points	Description
5	Inputs and outputs are crystal clear. Easy to verify correctness. For ML modules, metrics are well-reported and interpretable.
4	Inputs and outputs are clear with minor ambiguity. Assessment is straightforward.
3	Inputs and outputs defined but require effort to interpret or assess.
1	Inputs and outputs unclear. Difficult to determine what the module does or whether it works.
0	No clear I/O specification. Cannot assess functionality.

Does the module genuinely engage with the AI concept(s) it claims to cover?

Points	Description
6	Deep engagement with the topic. Demonstrates clear understanding. Implementation reflects core concepts accurately and meaningfully.
4	Solid engagement. Topic is addressed appropriately with minor superficiality.
2	Surface-level engagement. Topic is referenced but implementation does not demonstrate deep understanding.
1	Weak engagement. Topic is named but barely addressed in implementation.
0	No meaningful engagement with the stated topic.

Does the repository demonstrate professional development practices?

Points	Description
4	Excellent practices. Meaningful commit messages, appropriate use of pull requests, issues tracked, merge conflicts resolved thoughtfully.
3	Good practices. Most commits have meaningful messages. PRs used. Minor lapses.
2	Basic practices. Commits present but messages often vague. PRs or issues underutilized.
1	Poor practices. Commit messages uninformative. No PRs or issues. Repository is disorganized.
0	No meaningful use of GitHub practices.

Total points possible: 50