MicroSim Generation Workflow
This interactive swimlane flowchart illustrates the complete workflow from defining a learning objective to deploying a live MicroSim on an intelligent textbook. The diagram emphasizes the collaborative role between instructional designers and Claude Code skills in automating the generation process.
About This MicroSim
The workflow is organized into three swimlanes representing the key participants:
- Instructional Designer (Blue) - Human tasks including objective definition, concept analysis, library selection, specification writing, and quality testing
- Claude Code (Purple) - AI-assisted tasks including invoking the microsim-generator skill and iterating based on feedback
- MicroSim Files (Green) - Output artifacts including the generated HTML, JavaScript, CSS, and documentation files
Interactions: - Hover over any node to see a brief description and highlight connected steps - Click a node to lock the description panel for detailed reading - Click again or elsewhere to deselect
Workflow Steps Explained
| Step | Swimlane | Description |
|---|---|---|
| 1. Define Learning Objective | Designer | Identify what the learner should be able to do after completing the MicroSim |
| 2. Analyze Concept Type | Designer | Determine if the concept is a process, relationship, comparison, spatial, or data-focused |
| 3. Select Library Type | Designer | Choose appropriate library (p5.js, vis-network, Chart.js, etc.) based on concept type |
| 4. Write Specification | Designer | Create detailed spec with visual elements, interactions, and educational scaffolding |
| 5. Invoke MicroSim Generator Skill | Claude Code | The skill analyzes the spec and routes to the appropriate template |
| 6. Generate Files | MicroSim Files | Creates complete package: HTML, JS, CSS, index.md, and metadata.json |
| 7. Test in Browser | Designer | Test locally using mkdocs serve, check functionality and educational effectiveness |
| 8. Iterate with Feedback | Claude Code | If issues found, refine based on specific feedback |
| 9. Deploy to Textbook | MicroSim Files | Commit to repo and deploy via mkdocs gh-deploy |
| 10. MicroSim Live! | All | Available to learners on the published intelligent textbook |
Key Insights
- Human expertise guides AI - Clear specifications and quality criteria improve results
- Iteration is normal - Most MicroSims require 1-3 feedback cycles for optimal quality
- Skills automate patterns - Claude Code skills encode best practices for consistent output
- Testing validates learning - The ultimate measure is whether learners achieve the objective
Lesson Plan
Grade Level: Professional Development / Graduate
Duration: 30 minutes
Learning Objectives: - Understand the end-to-end workflow for creating educational MicroSims - Identify the roles of humans and AI in the generation process - Recognize decision points and iteration patterns in quality assurance
Activities:
- Explore the Workflow (5 min) - Click through each node to read descriptions
- Trace a Path (5 min) - Follow the happy path from start to "MicroSim Live!"
- Identify Feedback Loop (5 min) - Trace what happens when testing finds issues
- Discussion (10 min) - What makes a good specification? What feedback helps AI iterate effectively?
- Practice (5 min) - Draft a brief specification for a simple MicroSim concept
p5.js Editor Template
You can experiment with this code in the p5.js web editor.
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