planning-courses

name	planning-courses
description	Top-down course architecture from outcomes to modules. Use when designing a new course or restructuring an existing one.

Course Planning Skill

Triggering Contexts

• User wants to create a new course from scratch
• User feels an existing course is drifting or inconsistent
• User needs to restructure a curriculum
• User asks "what should this course cover?"

Core Principle

Outcomes first, topics second. Never start with "what should we teach?" Always start with "what should students be able to DO?"

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Workflow

Step 1: Define Course Identity

Ask for and document:

## Course Identity
- **Course Name:**
- **Duration:** (weeks, total hours, # sessions)
- **Format:** (lecture / workshop / hybrid / online / project-based)
- **Domain:** (e.g., investing, Bitcoin, programming)
- **One-line promise:** "After this course, students will be able to ____"

Step 2: Define Observable Outcomes

Outcomes must be observable and measurable, not vague.

❌ Vague	✅ Observable
"Understand technical analysis"	"Build a complete trading system using 3+ indicators"
"Learn about Bitcoin"	"Explain Bitcoin's monetary properties to a skeptic"
"Know risk management"	"Calculate position size given account size and stop loss"

Rule: Use action verbs. Build, Calculate, Design, Evaluate, Compare, Demonstrate, Explain, Create.

Ask the user to define 3-5 core outcomes. Fewer is better.

Step 3: Create Student Personas

Define 2-3 student profiles that represent the audience:

### Persona: [Name]
- **Background:** What they already know
- **Goal:** Why they're taking this course
- **Challenge:** What will be hardest for them
- **Success looks like:** What makes the course worth it for them

Why this matters: Every design decision should be checked against these personas. "Would Beginner Ben understand this? Would Advanced Amy be bored?"

Step 4: Map Modules to Outcomes

Create a module-outcome matrix:

Module	Outcome 1	Outcome 2	Outcome 3	Outcome 4
Module 1: Foundations	✅ Intro	✅ Intro
Module 2: Core Skills	✅ Build		✅ Intro
Module 3: Application		✅ Build	✅ Build	✅ Intro
Module 4: Mastery	✅ Assess	✅ Assess	✅ Build	✅ Assess

Every outcome must appear at least twice: once for learning, once for assessment. Every module must serve at least one outcome. Modules with no outcomes get cut.

Step 5: Sequence Modules

Check the sequence with these questions:

1. Does each module build on the previous one?
2. Are prerequisites taught before they're needed?
3. Is there a logical arc? (Foundation → Skill building → Application → Mastery)
4. Is the difficulty curve progressive, not flat or spiking?

Step 6: Design Assessment Strategy

Map assessments to outcomes:

Outcome	Assessment Type	When
"Build a trading system"	Project	Module 4
"Calculate position size"	Quiz / Exercise	Module 2
"Explain to a skeptic"	Presentation	Module 3

Rule: Every outcome must have at least one assessment. If you can't assess it, it's not a real outcome.

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Output: Course Blueprint

The final deliverable is a course-blueprint.md:

# [Course Name] Blueprint

## Course Identity
[From Step 1]

## Outcomes
1. [Observable outcome]
2. [Observable outcome]
3. [Observable outcome]

## Student Personas
[From Step 3]

## Module Structure
[Module-outcome matrix from Step 4]

### Module 1: [Name]
- **Sessions:** [N]
- **Outcomes served:** [list]
- **Key topics:** [brief]
- **Format mix:** [lecture %, workshop %, project %]

### Module 2: [Name]
...

## Assessment Map
[From Step 6]

## Prerequisite Chain
[Which modules depend on which]

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Red Flags to Call Out

• ⚠️ Orphan topic: Content that doesn't serve any outcome → Cut it
• ⚠️ Unassessed outcome: Outcome with no assessment → Add one
• ⚠️ Persona neglect: All content targets one persona → Rebalance
• ⚠️ Front-loaded theory: First 3+ sessions are all lecture → Add early hands-on
• ⚠️ Missing prerequisites: Module requires knowledge not taught yet → Resequence

Cross-References

• After blueprint is done → Use designing-classes for each session
• After all sessions designed → Use aligning-curriculum to check consistency