LATENT REFERENCES / TAG2
Elaboration
Original title: エラボレーション
This reference note belongs to Tag2 in Latent References, an archive curated by Keigo Yoshida. Its archive region is Pedestrian flow simulation. The note preserves its source text and links so that readers can trace the material behind the 3D map.
- Collection
- Tag2
- Archive region
- Pedestrian flow simulation
Archived reference note
English translation of the archived note. JP shows the original text. Source links and literal code are retained; the translation does not update or independently verify the source claims.
Elaboration is the process of adding detail to newly input information by relating new information being learned to existing knowledge. The elaboration process emphasizes How and Why behind the topic being learned rather than What is being learned.
エラボレーションとは、学習中の新しい情報を既存の知識と関連付けていくことで、新たにインプットしている情報に詳細を付け加えていくプロセスのことです。 エラボレーションのプロセスでは What (何を) 学習しているかよりも、学習中のトピックの背後にある How (どのように) や Why (なぜ) により重きを置きます。
Source updated 2023-12-03 · Snapshot 2026-10-08
Source links and calculated neighbors
Cosine values measure shared lexical features, not truth, agreement or identical meaning. Original reference links are labeled separately.
- CATIA: CAD SimulationComputed lexical cosine similarity 0.194 · shared title, text, tags and references
- Pedestrian Flow SimulationComputed lexical cosine similarity 0.171 · shared title, text, tags and references
- Reverse Simulation MusicComputed lexical cosine similarity 0.145 · shared title, text, tags and references
- JAX: TPUs, Physics Simulation and MoreComputed lexical cosine similarity 0.139 · shared title, text, tags and references
- The Age of Em: Work, Love, and Life When Robots Rule the EarthComputed lexical cosine similarity 0.120 · shared title, text, tags and references
- Chance OperationsComputed lexical cosine similarity 0.119 · shared title, text, tags and references
- ArticulationComputed lexical cosine similarity 0.117 · shared title, text, tags and references
- Social OrchestrationComputed lexical cosine similarity 0.111 · shared title, text, tags and references