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Spacing Effect

Memory improves when study sessions are spaced over time

The spacing effect is the well-replicated finding that learning is stronger when study sessions are separated by time instead of massed together. Spacing forces retrieval after partial forgetting, which strengthens the memory trace and improves long-term retention.

Spaced Repetition is essentially an algorithmic way to exploit this: it times reviews so that recall remains effortful but possible.

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147 Notes

  • -Across the Sprachraums
  • -Active Recall
  • -AI
  • -AI Slop
  • -AI-Induced Illusions of Competence
  • -Argumentative Act
  • -Argumentative Relations
  • -As We May Think
  • -Assumption
  • -Attack
  • -Bilingual Cognition
  • -Branched Resolution Map
  • -Claim
  • -Claim Lifecycle
  • -Claim Status Taxonomy
  • -Cognitive Agency Preservation
  • -Cognitive Exoskeleton
  • -Cognitive Sovereignty
  • -Confidence
  • -Contemplation Labor
  • -Contention
  • -Contention as Memorable Anchor
  • -Correction vs Drift
  • -Coscientist
  • -Counterexample
  • -Counterexample-First Search
  • -Creating Next-gen Digital Brains
  • -Cross-Linguistic Synthesis
  • -Dark Night of the Soul
  • -Definition Drift
  • -Desirable Difficulty in Verification
  • -Deskilling Through AI Delegation
  • -Dialectical Graph
  • -Dialectical Graph Edges
  • -Dialectical Graph Nodes
  • -Dialectical Interleaving
  • -Digital Brain
  • -Digital Garden
  • -Digital Jungle
  • -Document Collision
  • -Drift Phenomena
  • -Encyclopedia Galactica
  • -Encyclopedia Meltdown
  • -Environmental Drift
  • -Epistemic Protocol Layer
  • -Evidence Independence
  • -Evidence Span
  • -Exploration Mechanisms
  • -Exploration Strategies
  • -Extracranial
  • -Federated Knowledge Network
  • -Fluency Trap
  • -Forgetting Curve
  • -Foundation Fiction
  • -Friction as Enemy
  • -From Memex to Dialectical Graph
  • -From Preservation to Capability
  • -Galactic Empire
  • -GitHub for Scientists
  • -Graph as Meltdown Defense
  • -Graph Components
  • -Graph-Based Spaced Repetition
  • -Hallucination
  • -Hari Seldon
  • -Human Agency in AI
  • -Illusions of Competence
  • -Incompatibility Taxonomy
  • -Inference Layer
  • -Institutional Brain Rot
  • -Intellectual Companion
  • -Inter-Sprachraum Communication
  • -Interleaving
  • -Isaac Asimov
  • -Issue Node
  • -Knowledge Ark
  • -Knowledge Constitution
  • -Knowledge Failure Modes
  • -Knowledge Synthesis
  • -Knowledge System Layers
  • -Language-Agnostic Indexing
  • -Learning Science Principles
  • -LLM
  • -Low-Background Steel
  • -Meaning Loss
  • -Memex
  • -Meta-learning
  • -Method
  • -Method-Conclusion Coupling
  • -Minimum Contradiction Set
  • -Minimum Cut
  • -Model Collapse
  • -Monolith as Interface Metaphor
  • -Multi-AI Consensus Protocol
  • -Multilingual Knowledge Mesh
  • -Multilingual Memex
  • -Mystery and Minimalism
  • -Narrative Layer
  • -Natural Science Engineer
  • -Nonstationarity
  • -Normalized Proposition
  • -Operator
  • -Personal Knowledge Evolution
  • -Personal to Institutional Knowledge
  • -Pre-Contamination Resource
  • -Pre-LLM Text
  • -Project Aldehyde
  • -Project PIRI
  • -Provenance
  • -Psychohistory
  • -RAG
  • -RAG Limitations
  • -Rebuttal-First Search
  • -Relation Typing vs Similarity
  • -Replication Path Separation
  • -Responsibility Line
  • -Retrieval Practice
  • -Scapa Flow
  • -ScienceOps
  • -Scope
  • -Second Brain
  • -Seldon Plan
  • -Semantic Drift
  • -Signal Without Explanation
  • -Source
  • -Spaced Repetition
  • 01Spacing Effect (Currently Open at Position 1)
  • -Sprachraum
  • -Status Transition Rules
  • -Sunghyun Cho
  • -Superbrain
  • -Synthesis Mechanisms
  • -System Drift
  • -The Monolith
  • -Tokens ≠ Knowledge
  • -Traceability
  • -Training Data Contamination
  • -Translation Fidelity
  • -Translation Nuance Loss
  • -Triple Separation
  • -Un-Brain-Rotting
  • -Unanimity Requirement
  • -Undercut
  • -Vannevar Bush
  • -Verification
  • -Verification as Retrieval Practice
  • -Verification System
  • -Zero-Trust Ingestion