Learning Graph

The Learning Graph is the foundational data structure for the Learning Linux intelligent textbook. It maps the relationships between 550 concepts, showing how knowledge builds from foundational ideas to advanced applications.

Run the Learning Graph Viewer Fullscreen

What is a Learning Graph?

A learning graph is a directed acyclic graph (DAG) where:

• Nodes represent concepts students need to learn
• Edges represent prerequisite relationships ("you should learn A before B")
• Groups categorize concepts by topic area

This structure enables:

• Adaptive learning paths - Students can follow personalized routes through the material
• Prerequisite tracking - The system knows what foundations are needed for each topic
• Progress visualization - Students and instructors can see mastery across the concept map

Graph Statistics

Metric	Value
Total Concepts	550
Taxonomy Categories	16
Foundational Concepts	8
Maximum Chain Depth	12
Average Dependencies	1.72

Taxonomy Categories

The concepts are organized into 16 categories:

Category	Concepts	Description
History and Philosophy	20	UNIX origins, key figures, Linux distributions
Shell Fundamentals	30	Terminal, commands, navigation
File System	60	Directories, paths, file operations
Permissions	25	Access control, ownership, sudo
Text Processing	30	grep, regex, sed, awk, pipes
Text Editors	15	Nano, Vim
Configuration	20	Dotfiles, environment variables
Process Management	40	Processes, scheduling, scripts
Package Management	20	APT, Homebrew
Networking	50	IP, SSH, security, firewalls
Storage	65	Compression, devices, performance
Raspberry Pi	65	GPIO, sensors, IoT, automation
Cloud	25	Docker, Terraform, deployment
Development	25	Git, Python, IDEs
Administration	40	Users, services, display, audio
Capstone	30	Projects, careers

Files in This Section

• Concept List - Complete list of 550 concepts
• Concept Taxonomy - Category definitions
• Quality Metrics - Graph validation report
• Taxonomy Distribution - Category balance analysis

Data Files

• learning-graph.csv - Concepts with dependencies and taxonomy
• learning-graph.json - Complete graph in vis-network.js format
• metadata.json - Dublin Core metadata for the graph

Using the Learning Graph

For Students

The learning graph helps you understand:

1. What concepts you need to learn first (foundational concepts have no arrows pointing to them)
2. How topics connect to each other
3. Multiple paths to reach advanced topics

For Instructors

The learning graph supports:

1. Curriculum planning - See the full scope of topics
2. Prerequisite enforcement - Know what students need before each lesson
3. Progress monitoring - Track mastery across the concept map

For Developers

The learning-graph.json file can be:

1. Visualized with vis-network.js
2. Imported into learning management systems
3. Used for adaptive learning algorithms
4. Analyzed for curriculum optimization

Next Steps

After reviewing the learning graph:

1. Review concepts - Ensure all important topics are covered
2. Check dependencies - Verify prerequisite relationships make sense
3. Generate chapters - Use the book-chapter-generator skill to create chapter structure
4. Build content - Develop lessons for each concept

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Learning Graph generated with Learning Graph Generator v0.03 on 2025-12-06