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Learning Graph Quality Metrics Report

Overview

  • Total Concepts: 200
  • Foundational Concepts (no dependencies): 8
  • Concepts with Dependencies: 192
  • Average Dependencies per Concept: 1.18

Graph Structure Validation

  • Valid DAG Structure: ❌ No
  • Self-Dependencies: None detected ✅
  • Cycles Detected: 0

Foundational Concepts

These concepts have no prerequisites:

  • 1: Artificial Intelligence
  • 26: Intelligent Textbook
  • 37: Markdown Formatting Basics
  • 91: Taxonomy
  • 153: Git
  • 162: Visual Studio Code
  • 168: Python
  • 191: Command-Line Interface Basics

Dependency Chain Analysis

  • Maximum Dependency Chain Length: 11

Longest Learning Path:

  1. Intelligent Textbook (ID: 26)
  2. Learning Graph (ID: 39)
  3. Concept Nodes in Learning Graphs (ID: 40)
  4. Concept Dependencies (ID: 44)
  5. Dependency Mapping Process (ID: 70)
  6. CSV File Format for Graphs (ID: 71)
  7. vis-network JSON Format (ID: 99)
  8. JSON Schema for Learning Graphs (ID: 100)
  9. Metadata Section in JSON (ID: 101)
  10. Dublin Core Metadata (ID: 105)
  11. Title Metadata Field (ID: 106)

Orphaned Nodes Analysis

  • Total Orphaned Nodes: 104

Concepts that are not prerequisites for any other concept:

  • 3: Large Language Models Overview
  • 9: Skill Name and Description
  • 10: Skill License Information
  • 12: Skill Workflow Instructions
  • 14: Listing Available Skills
  • 16: Skill Execution Context
  • 18: Command Definition Files
  • 19: Installing Claude Commands
  • 20: Difference Between Skills & Commands
  • 23: Python Scripts in Skills
  • 24: Template Files in Skills
  • 25: Reference Documentation in Skills
  • 32: Level 5: AI Personalization
  • 36: Navigation Structure in MkDocs
  • 38: Admonitions in MkDocs
  • 43: Prerequisite Relationships
  • 45: Learning Pathways
  • 47: Target Audience Definition
  • 48: Course Prerequisites
  • 49: Main Topics Covered

...and 84 more

Connected Components

  • Number of Connected Components: 1

✅ All concepts are connected in a single graph.

Indegree Analysis

Top 10 concepts that are prerequisites for the most other concepts:

Rank Concept ID Concept Label Indegree
1 26 Intelligent Textbook 13
2 71 CSV File Format for Graphs 10
3 82 Quality Metrics for Graphs 8
4 53 Bloom's 2001 Revision 7
5 105 Dublin Core Metadata 7
6 6 Claude Skill 6
7 13 Installing a Claude Skill 6
8 39 Learning Graph 6
9 46 Course Description 6
10 116 ISO 11179 Standards 6

Outdegree Distribution

Dependencies Number of Concepts
0 8
1 166
2 22
3 3
8 1

Recommendations

  • ⚠️ Many orphaned nodes (104): Consider if these should be prerequisites for advanced concepts
  • ℹ️ Consider adding cross-dependencies: More connections could create richer learning pathways

Report generated by learning-graph-reports/analyze_graph.py