A love letter to flashcards

Use in Conceptual Domains (Math, Science, Chess, etc.)

• Several commenters use spaced repetition for higher math: especially memorizing definitions, lemmas, theorems, and representative problems.
• Some report that knowing all definitions/theorems by heart helped on exams, but they still struggled with proofs due to insufficient practice applying the knowledge.
• Others argue that if you need flashcards for basic definitions in analysis/group theory, you probably haven’t solved enough problems; repeated use can implicitly provide “spaced repetition.”
• For math/physics, suggestions include: break theorems into multiple cards, use problem-style cards that require solving, and keep a separate deck for time‑intensive “solve this” cards.
• Chess is learned via position images (tactics, endgames, openings) with the best move as the answer, updated periodically as rating changes.

Memorization vs Understanding

• One camp sees SRS as “drills” or foundation: essential for rapid recall of facts and procedures, on top of which understanding is built.
• Another camp worries that flashcards encourage shallow, test‑oriented learning and underweight conceptual mapping and mental models.
• Some counter that memorization and understanding are not either-or: memorizing even partially understood material can create a scaffold for later comprehension.
• Chunking and procedural fluency (e.g., being able to write code or do math without prompts) are cited as major benefits of active recall.

Language Learning Debates

• Heavy use of Anki for vocab is common; many report dramatic gains in retention compared to “natural” study.
• Others find naive word lists with translations inefficient and advocate sentence mining with rich context, often via cloze deletion cards.
• There’s disagreement on whether sentence cards are more or less efficient than single-word cards, and whether AI-generated sentences are good enough.
• Multiple commenters stress that SRS can’t replace large amounts of listening/reading, especially for listening comprehension and advanced nuance.

Tools, Algorithms, and Custom Systems

• Some praise Anki’s newer scheduling and flexibility; others prefer Leitner or write small custom SRS programs (often using open-source FSRS libraries).
• People repurpose flashcards for CLI commands, business facts, Emacs shortcuts, mental arithmetic, GTD-style reminders, and conceptual mapping tools.

LLMs and Automatic Card Generation

• Simple “paste a chapter, ask for cards” approaches are widely seen as producing impersonal, low‑value decks that still need heavy editing.
• More elaborate pipelines (tools, validation passes, AnkiConnect integration) reportedly yield high‑quality automated cards and reduce creation friction.
• Concerns remain that AI‑ or shared decks lose the personal context and cognitive work that make self-written cards powerful.

Motivation, Friction, and Limits

• Many find daily SRS hugely helpful mainly because it enforces consistency; others abandon it because reviews are aversive or feel like a chore.
• Some argue flashcard work need not be “fun,” only effective; others say if it feels dreadful, learners will quit, so card design and workload must be tuned.
• Flashcards are seen as excellent for certain goals (terminology-heavy fields, large vocabularies, factual scaffolding) but limited for skills requiring deep fluency, creativity, or rich, contextual understanding unless combined with other practice.