Course redesign analyst
Skill alainlebret/claude-agents/higher-ed-teaching-agents/skills/course-redesign-analyst
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Audits and redesigns existing courses, labs, and assessments by identifying weaknesses in progression, exactitude, workload, and alignment. Use when an existing course must be improved rather than created from scratch.
SKILL.md
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Course Redesign Analyst
Goal
Analyse an existing course and produce a structured redesign plan that addresses identified weaknesses without discarding what already works. The analysis must be evidence-based: every criticism must cite a specific artefact, section, or exercise.
When to use
- When the
redesign-existing-courseworkflow is triggered. - When an instructor provides existing slides, TPs, or exams and says « this isn't working ».
- When student failure rates, feedback, or exam results point to systemic issues.
Inputs
Collect as many of the following as are available:
- Existing course materials (slides, handouts, TD/TP statements)
- Existing exams and rubrics
mission.json(if already defined) or an informal description of the course goals- Student feedback or failure-rate data (if available)
- Institutional constraints (hours, tools, level)
Output contract
| File | Description |
|---|---|
redesign-audit.md | Structured audit: findings per dimension, severity, evidence |
redesign-plan.md | Prioritised list of changes with rationale and effort estimate |
mission.json (updated or created) | Revised pedagogical specification aligned with redesign goals |
redesign-audit.md structure
# Course Redesign Audit — <course title>
## Dimension: Progression and sequencing
### Findings
- [CRITICAL] <finding> — Evidence: <section/exercise/slide>
- [MODERATE] ...
## Dimension: Scientific exactitude
...
## Dimension: Workload and feasibility
...
## Dimension: Assessment alignment
...
## Dimension: Prerequisite coherence
...
## Summary
<Overall assessment: what works, what must change, what is optional>
Audit dimensions
| Dimension | What to examine |
|---|---|
| Progression | Are concepts introduced in logical dependency order? Are there conceptual jumps? |
| Scientific exactitude | Are technical claims accurate? Are deprecated APIs or outdated practices taught? |
| Workload | Are TP/exam durations realistic? Is homework load calibrated to the academic level? |
| Assessment alignment | Does each exam question map to a taught learning outcome? |
| Prerequisite coherence | Does the course assume knowledge not stated in prerequisites? |
| Redundancy | Are the same concepts repeated without deepening? Are there contradictory explanations across sessions? |
Rules
- Never recommend removing content without stating what learning outcome is lost and whether it matters.
- Prioritise changes by impact: fix alignment and exactitude first, then workload, then style.
- Estimate effort per change:
low(< 2h),medium(2–8h),high(> 8h). - If student data is available, use it. Do not speculate about failure causes when evidence exists.
- Produce a
mission.jsonthat reflects what the course should be, not what it currently is.