Semester 0: Orientation: Rubric and Passing Standards
The World-Class Strand evidence is non-compensatory: every required category must pass even when the rest of the submission is strong.
This rubric applies to the semester-level checkpoint, exam, and project. Use it with the answer key and solution outlines to keep grading consistent and learner-visible.
Minimum Passing Standard
To pass Semester 0: Orientation, the learner must satisfy all of the following:
- Checkpoint: at least 80% of checkpoint prompts are answered correctly and independently, with no critical gaps in CS orientation, algorithm exploration, computing maps, and disciplined learning workflow.
- Exam: overall score is at least 70%, and no major section that tests a core semester outcome is below 60%.
- Project: all required deliverables are present, the artifact can be inspected or reproduced by another person, and the learner can defend the main tradeoffs.
- Programming and prerequisites: all five Module 0 dimensions score 2/2; clinic and both retention checks pass; algebra and notation gates close. Every required strand category passes independently.
- Integrity: sources, collaboration, generated assistance, and borrowed code or examples are acknowledged.
- Remediation: a conditional pass remains incomplete until the required repair is demonstrated on a fresh case; revisiting a page alone is insufficient.
Failure in any one of these categories means the semester should not be marked complete yet, even if the other artifacts look strong.
Grading Rubric
| Dimension | Needs repair | Minimum pass | Strong pass | Excellent / portfolio-ready |
|---|---|---|---|---|
| Concept command | Uses terms loosely or confuses core ideas. | Defines and applies the required concepts with minor gaps. | Explains concepts through examples, counterexamples, and constraints. | Teaches the ideas clearly and connects them across semesters. |
| Reasoning quality | Jumps to answers; hides assumptions. | Shows enough steps to inspect correctness. | Makes assumptions, invariants, and tradeoffs explicit. | Compares alternatives and anticipates edge cases or objections. |
| Evidence | Claims are unsupported or impossible to reproduce. | Provides basic proofs, tests, diagrams, traces, or outputs. | Evidence targets the riskiest claims and is easy to verify. | Evidence is organized as a review packet a third party can audit. |
| Semester integration | Treats modules as unrelated topics. | Connects the main semester themes to the assessment. | Synthesizes multiple modules in one coherent explanation or artifact. | Shows how mastery of CS orientation, algorithm exploration, computing maps, and disciplined learning workflow shapes engineering judgment beyond the course examples. |
| Communication | Hard to follow; missing context. | Understandable and complete enough to grade. | Clear structure, named decisions, and concise explanations. | Professional presentation with honest limitations and next steps. |
Strong Submission Traits
Strong submissions usually demonstrate these traits:
- concise explanations that reveal the mental model, not just the final answer
- concrete artifacts that can be run, checked, reviewed, or traced
- explicit handling of edge cases, constraints, and failure modes
- visible revision: mistakes were found, corrected, and documented
- appropriate connections between CS orientation, algorithm exploration, computing maps, and disciplined learning workflow and prior semester foundations
Common Weak Submission Patterns
Watch for these patterns during self-review:
- vocabulary recognition without the ability to apply the idea to a new prompt
- impressive-looking diagrams, code, or prose with no verification evidence
- hidden dependencies on tutorials, solution videos, or AI-generated answers
- project scope that is too broad to inspect or too narrow to prove the required skill
- missing reflection about tradeoffs, limitations, or what would be done differently
Calibration Decision Guide
- Pass: all minimum standards are met and weak patterns are minor.
- Conditional pass: the artifact is mostly sound, but one bounded repair is required before moving to Semester 1.
- Repeat / revisit: a core concept, core deliverable, or integrity requirement is missing.
When uncertain, grade against evidence rather than effort. Time spent is useful context, but the semester is complete only when the learner can demonstrate the outcomes.
Workload and advancement contract
Use Workload and Progression for the complete hour allocation, prerequisite order, evidence reuse, score thresholds and repair rules. Its estimates do not establish learner-tested duration. All required gates apply together; conditional pass means repair remains, not permission to skip a gate.
Learning-support dimensions
Also require L1–L3 at 2/2 plus the already-assessed Launchpad preparation record under their module-specific criteria. These do not change the technical rubric or replace its requirements. Score observable decisions and evidence, not motivation, confidence, personal disclosure or a perfect streak. Preserve failed and repaired attempts; all gates must close before advancement.
Technical practice dimensions
Also require all twelve technical dimensions: DF1–DF4, WH1–WH4 and AI1–AI4 at 2/2. The executable checks do not grade explanations or changed-requirement transfer. The live HTTP gate remains pending if local networking cannot run. Offline AI practice is explicitly permitted and must be labeled as authored/simulated evidence.