Adapting and teaching the capstone¶
The public seven-phase guide is the default project. Preserve its outcome coverage when adapting the context or tools; document the changes students need to follow. Use the session guide and adoption checklist for preparation and pilots.
Decisions before teaching¶
| Decision | Recommended default | Adaptation boundary |
|---|---|---|
| Context | Supplied fictional retail interview | Another industry needs revised requirements, assumptions and synthetic data; do not assume the same regulatory applicability. |
| Team structure | Small teams; individual final reflection | Individual learners may complete all artifacts; team roles and contribution records remain private. |
| Tools | Local PostgreSQL/dbt baseline | Substitute tools only with equivalent outcome evidence and a tested access route. |
| Evidence | Design plus scoped lab observations | Require a separate implementation only with explicit scope, time and assessment guidance. |
| AI | Support-prioritization teaching extension and purpose-change review | Preserve bias, transparency, accountability and lifecycle reasoning; model training is not required. |
| Delivery | Text or accessible diagrams; optional redacted screenshots | Assess the concept consistently across accessible evidence formats. |
Feedback checkpoints¶
After Phase 1, check source traceability and unresolved questions. After Phase 2, check grain, cardinality and consistency with requirements. After Phases 3–4, check workload tradeoffs, retention rationale, owner assignments and permitted AI use. After Phase 5, check evidence labels and complete peer review before the defense. Return feedback in time for revision; record changes rather than freezing an early mistake.
Use the public descriptors to calibrate two sample responses privately before grading. Do not treat runner success as proof of understanding. During the defense ask each student to explain a changed condition, an unsupported claim and a next verification. Keep official weights, dates, assignment links, solutions and grading records in the LMS.
Scope and readiness¶
The core supplies local permission checks, client observations and labeled simulations. Optional Labs 12–14 add server CSV logging, verified transport encryption and two separate local instances with batch transfer. They do not demonstrate production scalability, independent audit storage, automatic failover or storage encryption. For the Spring 2026 syllabus, assess Module 4 through administrative comparison; use Optional Lab 13 for enrichment. Specify hands-on encryption evidence for Module 5 and identify the catalog/workflow activities assigned in Modules 1 and 3. Discussion and executed controls provide different assessment evidence.
Do not require platform badges or public student repositories merely to adopt this project. External workshop expectations must be specified separately in the LMS. Publish student examples only with appropriate permission and accurate attribution. Retain Isaac K. Nti's original course credit and identify your adaptations.
Author: Isaac K. Nti. Citation and reuse terms.