Learning Graph for US Government¶
Open Learning Graph Viewer Fullscreen (Recommended)
This section contains the learning graph for this textbook. A learning graph is a graph of concepts used in this textbook. Each concept is represented by a node in a network graph. Concepts are connected by directed edges that indicate what concepts each node depends on before that concept is understood by the student.
A learning graph is the foundational data structure for intelligent textbooks that can recommend learning paths. A learning graph is like a roadmap of concepts to help students arrive at their learning goals.
At the left of the learning graph are prerequisite or foundational concepts. They have no outbound edges — they only have inbound edges for concepts that depend on understanding them first. At the far right we have the most advanced concepts in the course. To master these concepts you must understand all the concepts that they point to.
The US Government learning graph contains 200 concepts organized into 12 taxonomy categories, connected by 362 dependency edges, with a maximum learning path of 15 concepts from foundational to advanced.
Course Description¶
We use the Course Description as the source document for the concepts included in this course. The course description uses the 2001 Bloom's Taxonomy to order learning objectives, and is aligned with the College Board AP US Government and Politics curriculum framework.
List of Concepts¶
Generative AI converted the course description into a Concept List. Each concept is in the form of a short Title Case label with most labels under 32 characters long. 200 concepts span 11 content units plus four cross-cutting civic skill concepts.
Concept Dependency List¶
The dependency graph is provided in two formats. The CSV file
contains columns ConceptID, ConceptLabel, Dependencies (pipe-delimited
prerequisite IDs), and TaxonomyID. The JSON file
uses the vis-network JavaScript library format with metadata, groups,
nodes, and edges sections — ready to drop into the interactive graph viewer.
Analysis and Documentation¶
Course Description Quality Assessment¶
Quality review of course-description.md for learning graph generation.
- Course description fields and content depth analysis
- Validates sufficient depth for 200+ concepts
- Bloom's Taxonomy coverage check
- Score: 100/100 — Excellent
View the Course Description Quality Assessment
Learning Graph Quality Validation¶
Overall quality assessment of the generated dependency graph.
- Valid DAG structure (0 cycles detected) ✅
- 3 foundational entry points (Enlightenment Philosophy, Articles of Confederation, Critical Thinking in Civics)
- 0 orphaned nodes — all 200 concepts are connected ✅
- 362 dependency edges, average 1.84 per concept
- Maximum dependency chain length: 15 steps
- Graph quality score: 88/100
View the Learning Graph Quality Validation
Concept Taxonomy¶
12 color-coded categories assign each concept to a primary classifier for visualization in the graph viewer.
- FOUND — Foundations of American Democracy (SteelBlue)
- CONST — The Constitution (DarkSlateBlue)
- FED — Federalism (DarkGreen)
- CONG — Congress (Teal)
- PRES — The Presidency (DodgerBlue)
- BURO — The Federal Bureaucracy (OliveDrab)
- JUDI — The Federal Judiciary (MediumPurple)
- CLIB — Civil Liberties and Civil Rights (Crimson)
- OPIN — Political Opinion and Media (Gold)
- ELEC — Elections and Political Participation (DarkGoldenrod)
- AIGOV — AI and Government (Orange)
- CRIT — Critical Thinking and Civic Skills (DeepPink)
Taxonomy Distribution¶
Statistical breakdown of concepts per category with balance verification. No category exceeds 30% of total concepts.