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Hashcards: A Plain-Text Spaced Repetition System
17 hours ago
- hashcards is a local-first spaced repetition app using Markdown files instead of a database.
- Cards are content-addressed by hash, stored as directories of .md files with Q/A and cloze formats.
- Benefits include editing with any editor, version control with Git, sharing on GitHub, and scripting with Unix tools.
- The app uses FSRS scheduling algorithm for optimal review intervals.
- Frictionless card creation is prioritized, with minimal markup for cloze deletions (square brackets) and Q/A cards.
- Compared to Anki, hashcards avoids its poor interface and WYSIWYG editing; compared to Mochi, it addresses verbose cloze syntax and algorithmic issues.
- User frustrations with Anki (ugly interface, lack of direct study mode) and Mochi (poor long-term scheduling) drove design decisions.
The Applicability of Spaced Repetition
17 hours ago
- Spaced repetition works best for systematically organized key-value mappings with short keys and values, such as the NATO phonetic alphabet or periodic table.
- For biology and language learning, spaced repetition is effective because the underlying conceptual models (e.g., 3D shapes in biology, a language center in the brain) come naturally, leaving mostly facts to memorize.
- Highly conceptual knowledge like math is difficult to encode into flashcards because it requires building a mental model first, and creating short, unambiguous questions from abstract facts is challenging.
- Relational facts (e.g., 'caffeine is metabolized by CYP1A2') are easier to encode as binary predicates, while stand-alone assertions (e.g., 'all unitary matrices are invertible') are problematic because simple yes/no questions are biased and broader questions are ambiguous.
- Using AI to write flashcards is often misguided because it cannot access an individual's internal mental model, what they already know, or which facts need more reinforcement.
- The author suggests that case studies showing how to turn textbook passages into flashcards could help derive general rules for encoding complex conceptual knowledge.
Entropic Thoughts
17 hours ago
- Spaced repetition is a powerful memory tool accessible to anyone, requiring only minutes daily.
- The four steps: add flashcards, see question, recall answer, rate success.
- Writing good flashcards is the most critical skill; software and algorithm choice are secondary.
- Active recall requires trying to retrieve the answer before seeing it and being honest about success.
- Pre-made decks are discouraged because they don't integrate with your existing knowledge.
- Manual card creation itself provides significant learning benefits, not just time wasted.
- Spaced repetition can build deep understanding by probing concepts from multiple angles.
- Memorizing basics enhances meaningful practice by reducing lookup time.
- It works for both long-term retention and quick short-term learning for new projects.
- Keep sessions short (e.g., 15 cards or 5 minutes) to maintain habit.
- Backlogs are manageable; resume without guilt.
- If frustrated, focus on improving flashcard quality.
- Spaced repetition applies to diverse fields like software, math, human interaction, and more.
- Update or reword flashcards to prevent rote memorization of clues.

spaced repetition

Hashcards: A Plain-Text Spaced Repetition System

The Applicability of Spaced Repetition

Entropic Thoughts