Concept Map

Domain vocabulary as falsifiable propositions. The title is a Guiding Question that decides what belongs on the map, and every

Concept → Relation → Concept chain must read as a falsifiable sentence.

Node types

• Concept — a concept or term
• EmphasizedConcept — an important concept to highlight
• Relation — a linking verb or phrase connecting concepts, forming propositions of the shape Concept → Relation → Concept

Edge types

• concept_to_relation — Concept → Relation (tail marker only)
• relation_to_concept — Relation → Concept (arrow head only)
• emphasized_concept_to_relation — EmphasizedConcept → Relation
• relation_to_emphasized_concept — Relation → EmphasizedConcept

EmphasizedConcept takes its own pair, so an emphasized concept in a chain needs those rather than the plain ones. Both are inferred, so this only matters when naming a type explicitly.

vgraph learningCM: ConceptMap "What is Learning?" {
    node student: Concept "Student";
    node subject: Concept "Subject";
    node practice: EmphasizedConcept "Practice";
    node understanding: Concept "Understanding";

    node learns: Relation "learns";
    node requires: Relation "requires";
    node leads_to: Relation "leads to";

    edge student -> learns;
    edge learns -> subject;
    edge subject -> requires;
    edge requires -> practice;
    edge practice -> leads_to;
    edge leads_to -> understanding;
}

Relationships are nodes rather than edge labels, which is what makes the propositions readable: "Student learns Subject", "Subject requires Practice". Never leave a concept unconnected. Reuse a single Relation node when several concepts share it ("Dog is a Mammal", "Cat is a Mammal") — but note that a relation with both multiple inbound and multiple outbound edges asserts every combination: all n × m propositions must be valid. If any is circular or meaningless, split the relation.

The editor's ConceptMap — How Learning Works is a variant of this map that names every edge type explicitly, including the EmphasizedConcept pair.