188 Concept Taxonomy 5dd5a716

# Concept Taxonomy

**Course:** Using Claude Skills to Create Intelligent Textbooks
**Total Categories:** 12
**Generated:** 2025-11-08

## Taxonomy Categories

### 1. AI Foundations
**TaxonomyID:** AIFND

**Description:** Core concepts related to artificial intelligence, large language models, Claude AI, and prompt engineering fundamentals.

**Includes:**
- AI basics and terminology
- Claude AI and Claude Pro
- Large language models
- Prompt engineering principles
- Token management
- Usage optimization

---

### 2. Claude Skills System
**TaxonomyID:** SKILL

**Description:** Concepts related to creating, installing, managing, and executing Claude Skills and Commands.

**Includes:**
- Skill definition and structure
- YAML frontmatter
- Skill installation and invocation
- Claude Commands
- Skill packaging and distribution
- Testing and debugging
- Security and permissions

---

### 3. Intelligent Textbooks
**TaxonomyID:** IBOOK

**Description:** Core concepts about intelligent textbooks, their levels of intelligence, and the overall creation workflow.

**Includes:**
- What intelligent textbooks are
- Five levels of intelligence
- Textbook workflows
- Chapter and section structure
- Content organization
- Reading level appropriateness

---

### 4. MkDocs Platform
**TaxonomyID:** MKDOC

**Description:** Concepts related to MkDocs documentation generator, Material theme, and Markdown formatting.

**Includes:**
- MkDocs basics
- Material for MkDocs theme
- Configuration files
- Navigation structure
- Markdown formatting
- Admonitions
- GitHub Pages deployment

---

### 5. Learning Graphs
**TaxonomyID:** GRAPH

**Description:** Concepts related to learning graphs, concept dependencies, DAG structures, and graph quality metrics.

**Includes:**
- Learning graph fundamentals
- Concept nodes and edges
- Dependencies and prerequisites
- DAG (Directed Acyclic Graph)
- Graph validation
- Quality metrics
- Visualization formats

---

### 6. Educational Theory
**TaxonomyID:** EDTHY

**Description:** Educational frameworks, learning theories, and pedagogical principles including Bloom's Taxonomy and course design.

**Includes:**
- Bloom's Taxonomy (2001 revision)
- Six cognitive levels
- Learning outcomes design
- Course descriptions
- Action verbs
- Prerequisites and audience

---

### 7. Content Creation
**TaxonomyID:** CONTE

**Description:** Concepts related to generating and organizing educational content, chapters, and instructional materials.

**Includes:**
- Content generation processes
- Chapter structure
- Section organization
- Worked examples
- Practice exercises
- Chapter index files

---

### 8. Educational Resources
**TaxonomyID:** RSRCE

**Description:** Supplementary educational materials including glossaries, FAQs, quizzes, and reference lists.

**Includes:**
- Glossary generation
- ISO 11179 standards for definitions
- FAQ creation
- Quiz generation
- Multiple-choice questions
- Assessment design

---

### 9. Interactive Elements
**TaxonomyID:** INTER

**Description:** Interactive simulations, MicroSims, and dynamic educational content using p5.js and other libraries.

**Includes:**
- MicroSims concept and structure
- p5.js library
- Interactive simulations
- Interactive controls (sliders, buttons)
- Seeded randomness
- Iframe embedding

---

### 10. Version Control
**TaxonomyID:** VERCT

**Description:** Git version control, repository management, and deployment workflows for educational content.

**Includes:**
- Git basics
- Version control concepts
- Git commands (status, add, commit, push)
- GitHub integration
- Repository structure
- GitHub Pages deployment

---

### 11. Development Tools
**TaxonomyID:** TOOLS

**Description:** Development environments, command-line interfaces, terminals, and shell scripting tools.

**Includes:**
- Visual Studio Code
- Command-line interface basics
- Terminal operations
- Bash shell
- Shell scripts
- Directory navigation
- File operations

---

### 12. Data & Scripting
**TaxonomyID:** DATAS

**Description:** Data formats, scripting languages, file processing, and metadata standards used in the textbook workflow.

**Includes:**
- Python programming
- Python scripts for data processing
- CSV file format
- JSON format and schema
- Dublin Core metadata
- pip package management
- Taxonomy categorization
- Data validation scripts

---

## Category Distribution Guidelines

- Target: ~16-17 concepts per category (200 concepts ÷ 12 categories)
- Maximum: 30% of total concepts (~60 concepts)
- Minimum: 5% of total concepts (~10 concepts)
- Use **MISC** for concepts that don't fit clearly into defined categories

## Notes

This taxonomy provides a balanced organization of course concepts across technical, pedagogical, and practical domains. Categories are designed to:
1. Avoid excessive overlap
2. Maintain clear boundaries
3. Support logical learning progressions
4. Enable effective visualization with distinct colors
5. Align with the course structure and learning outcomes