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Intelligent Textbook Creation Workshop

Duration: 2 hours

Prerequisites: - Course description prepared - Claude Code installed with all skills loaded and usage visible - Users know how to check and extend their own token usage: https://claude.ai/settings/usage - Basic familiarity with markdown and command-line tools

Workshop Goal: By the end of this workshop, participants will understand the intelligent textbook creation workflow and have generated core components for their own textbook using Claude skills.

Workshop Outline

Part 1: Introduction & Setup (15 minutes)

1.1 Welcome & Overview (5 min)

  • What are intelligent textbooks? (5 levels of intelligence)
  • Why use Claude skills for textbook creation?
  • Workshop structure and expected outcomes

1.2 Environment Setup (10 min)

  • Verify Claude Code installation
  • List available skills with /skills command
  • Review course description format
  • Clone starter template or create new MkDocs project

Hands-on: Each participant runs ./scripts/list-skills.sh and verifies their course description file exists.

Part 2: Foundation - Course Description & Learning Graph (30 minutes)

2.1 Course Description Quality (10 min)

  • Components of a quality course description
  • ISO 11179 standards for definitions
  • Bloom's Taxonomy integration

Demo: Use /skill course-description-analyzer on sample course description

Hands-on: Participants analyze their own course descriptions and refine based on feedback

2.2 Learning Graph Generation (20 min)

  • What is a learning graph? (concepts + dependencies)
  • DAG (Directed Acyclic Graph) constraints
  • Taxonomy categorization (12 categories)
  • Quality metrics interpretation

Demo: 1. Generate learning graph with /skill learning-graph-generator 2. Review generated files in docs/learning-graph/: - learning-graph.csv (concept list with dependencies) - quality-metrics.md (validation report) - learning-graph.json (vis-network visualization data)

Hands-on: Each participant generates their learning graph and reviews quality metrics

Part 3: Content Generation Workflow (40 minutes)

3.1 Glossary Creation (10 min)

  • ISO 11179 definition standards (precise, concise, distinct, non-circular)
  • Automatic glossary generation from concept list

Demo: Use /skill glossary-generator to create docs/glossary.md

Hands-on: Participants generate glossaries and review 3-5 definitions for quality

3.2 Chapter Structure Planning (10 min)

  • Concept-to-chapter mapping
  • Respecting dependency order
  • Balancing chapter length and complexity

Demo: Use /skill book-chapter-generator to create chapter structure

Discussion: How were concepts distributed across chapters? Does the ordering make pedagogical sense?

3.3 Chapter Content Generation (15 min)

  • Content generation at appropriate reading level
  • Bloom's Taxonomy level distribution
  • Non-text elements (diagrams, infographics, MicroSims)

Demo: Generate content for one chapter with /skill chapter-content-generator

Review together: - Markdown structure and formatting - Admonitions and callouts - Practice problems and worked examples

Hands-on: Participants generate content for their first chapter

3.4 Quiz Generation (5 min)

  • Bloom's Taxonomy-aligned questions
  • Concept mapping to learning graph
  • Interactive quiz format

Demo: Use /skill quiz-generator for a sample chapter

Hands-on: Participants generate quiz for their first chapter

Part 4: Interactive Elements - MicroSims (25 minutes)

4.1 Introduction to MicroSims (5 min)

  • What are MicroSims? (interactive p5.js simulations)
  • MicroSim directory structure (docs/sims/[sim-name]/)
  • Educational value of interactivity

4.2 p5.js MicroSim Creation (10 min)

  • Two-region pattern (drawing canvas + controls)
  • Seeded randomness for reproducibility
  • Iframe embedding in chapter content

Demo: Create a simple MicroSim with /skill microsim-p5 - Example: Visualizing slope and y-intercept changes in linear equations - Show main.html structure - Show index.md documentation with iframe

4.3 Alternative Visualization Skills (10 min)

  • Chart.js - data visualizations (bar, line, pie charts)
  • Mermaid - flowcharts and process diagrams
  • Timeline - chronological event sequences
  • Venn diagrams - set relationships
  • Maps - geographic visualizations

Demo: Quick examples of 2-3 different visualization types

Discussion: Which visualization types best suit different subject areas?

Part 5: Quality Assurance & Deployment (10 minutes)

5.1 Metrics & Validation (5 min)

  • Book metrics generation (word counts, concept coverage)
  • Chapter-level metrics
  • Quality score interpretation

Demo: Use /skill book-metrics-generator to create comprehensive metrics report

5.2 Site Building & Deployment (5 min)

  • MkDocs build process
  • Local preview with mkdocs serve
  • GitHub Pages deployment with mkdocs gh-deploy

Demo: Build and preview site locally

Hands-on: Participants preview their textbook site at http://localhost:8000

Part 6: Wrap-up & Next Steps (10 minutes)

6.1 Complete Workflow Review (5 min)

The 12-step intelligent textbook workflow:

  1. Course Description Development
  2. Bloom's Taxonomy Integration
  3. Concept Enumeration (200 concepts)
  4. Concept Dependencies (DAG)
  5. Concept Taxonomy Categorization
  6. Learning Graph Visualization
  7. Chapter/Section Structure
  8. Chapter Content Generation
  9. MicroSim Creation
  10. Glossary & FAQ Generation
  11. Quality Assurance (metrics)
  12. Site Deployment

6.2 Advanced Topics & Resources (3 min)

  • FAQ generation from course content
  • Reference list generation
  • Custom skill creation
  • Contributing to the skills repository

6.3 Q&A and Troubleshooting (2 min)

  • Common issues and solutions
  • Where to get help (GitHub issues, documentation)

Workshop Materials Checklist

Before the workshop: - [ ] Sample course descriptions (3-4 different subjects) - [ ] Claude Code installed on all machines - [ ] Skills repository cloned and installed - [ ] MkDocs and Material theme installed - [ ] Python environment with required packages

Handouts: - [ ] Quick reference card with all skill commands - [ ] Bloom's Taxonomy cognitive levels chart - [ ] ISO 11179 definition standards checklist - [ ] Troubleshooting guide

Sample Projects: - [ ] Complete example textbook (e.g., "Introduction to Programming") - [ ] Partially completed textbook for hands-on practice - [ ] Template course-description.md files

Post-Workshop Follow-up

Immediate next steps for participants: 1. Complete chapter generation for remaining chapters 2. Generate FAQs with /skill faq-generator 3. Create 5-10 MicroSims for key concepts 4. Run quality metrics and address gaps 5. Deploy to GitHub Pages

Extended learning: - Join the Claude skills community - Contribute new skills or improvements - Share completed textbooks for peer review - Explore Level 4+ intelligence features (adaptive learning)

Facilitator Notes

Time Management: - Parts 1-2 must stay on schedule (foundation is critical) - Part 3 can flex ±5 minutes based on group needs - Part 4 is most likely to run over - have backup time - Part 6 can be shortened if needed

Common Issues: - Learning graph generation may fail if course description lacks detail - Quality scores <70 require iteration on concept enumeration - Circular dependencies in graphs require manual CSV editing - MicroSim generation requires clear concept specifications

Engagement Strategies: - Pair programming during hands-on sections - Share screens to show different subject area examples - Use chat for questions during demos - Create shared document for troubleshooting tips

Success Metrics: - 80%+ participants generate a learning graph - 60%+ participants generate at least one chapter - 100% participants can preview their site locally - Post-workshop survey shows confidence in using skills independently