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 รท 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