Flashcards

Spaced repetition systems

January 2, 2015 — April 14, 2025

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Here are some practical notes for my own personal usage.

1 Theory

More on the theory and background has been written by others. An example of integrating flashcards into an intensive learning system for theorems and mathematics is here.

For a virtuosic example of integrating flashcards into a self-learning project, see Isaak’s 12 Months of Mandarin and Methods of Mandarin.

To do: add theory of anchors, phonetic encodings, optimal scheduling for Spaced Repetition…

2 Scheduling algorithms

FSRS seems to be good. See open-spaced-repetition/fsrs4anki: A modern Anki custom scheduling based on Free Spaced Repetition Scheduler algorithm. Note the heartwarming origin story:

Hi, I’m Jarrett Ye, the creator of FSRS. FSRS is a highly efficient spaced repetition algorithm used by many people worldwide, saving considerable time. It applies cognitive science and educational technology to help students learn more effectively.

However, most Chinese high school students are still forced to study “611” — from 6 AM to 11 PM, six days a week. Tragically, many students have committed suicide or developed serious mental health issues.

The 611Study. ICU project aims to stop this abusive study model and protect students’ lives and health.

As a former Chinese student, I experienced overtime study and sleep deprivation during high school. Anki saved my life. I want to use this algorithm to save more lives, but most Chinese high schools still prevent students from using it.

I hope this project can raise awareness and help more students.

Wow! This author deserves your citations (Su et al. 2023; Ye, Su, and Cao 2022).

I believe this is now Anki-native as per fsrs4anki/docs/tutorial.md.

3 Minimal pair tests for learning language sounds

See How to Teach Old Ears New Tricks:

With a handful of recordings […] (freely accessible through Web sites such as Rhinospike and Forvo) and with testing software such as Anki, you can build powerful ear-training tools for yourself. These are tools that, after just a few hours of use, will make foreign words easier to hear and easier to remember, and they may give you the edge you need to finally learn the languages you’ve always wanted to learn.

Fascinatingly,

Some of the best data on this phenomenon come from studies of Japanese adults learning to hear the difference between r and l. Why the Japanese? For one, because the r-versus-l problem is notorious; Japanese speakers tend to do little better than chance when attempting to tell their rocks from their locks. Second, they know they have this difficulty, and many will happily volunteer to come into a research laboratory— whereas English speakers do not care much about learning the difference between Hindi’s four nearly identical-sounding d’s.

4 Anki

My workhorse tool. A powerful albeit geeky option. See the Anki website. Anki is open source and has a large community of users and developers. It is very flexible and a little bit ugly.

Anki LaTeX notes importer
Anki for mathematics
AnkiConnect

AnkiConnect enables external applications such as Yomichan to communicate with Anki over a simple HTTP API. Its capabilities include executing queries against the user’s card deck, automatically creating new cards, and more.

Useful infrastructure that makes it easy to programmatically edit your flashcards without building a whole new plugin.
AnkiAIUtils: AI-Powered Visual Mnemonics for Anki Cards / thiswillbeyourgithub/AnkiAIUtils

This one augments your troublesome cards with extra AI mnemonics. Their image mnemonics feature (illustrator.py) is the AI+Anki feature that I want, but it didn’t work for me, so I forked the code and made some changes.
ValeriiZhyla/anki-cards-ai-generator

This one generates new flashcards for you using LLMs. Especially supports German and English languages and knows about CERF language levels
Anki AI - Enhance Your Flashcards with ChatGPT and other LLMs / rroessler1/anki-ai-field-generator

Interactively adds fields from LLMs to your cards inside the app.

5 Mnemosyne

The Mnemosyne Project

Mnemosyne aims to be a user-friendly flash card program, with a clean, deceptively simple interface that does not require you to wrap your head around complicated concepts before you can start using it. At the same time, under the hood it is very powerful, and its architecture allows infinite extensibility and customisibility through plugins and a scripting API, for the benefit of power users.

Source code here. Mnemosyne also looks good but I have never used it, preferring the Anki community and iOS support. Mnemosyne is desktop-and-android only.

These days it resembles Anki closely.

6 Rember

Rember — Create amazing flashcards with AI

Rember is a simple yet powerful spaced repetition system designed to help you remember more.

Manually creating flashcards is tedious and time-consuming. Rember uses AI to create cards automatically from your content. Easily tweak them in our editor to make them just right.

USD8/month. At time of writing it does not support importing cards from other systems, and I have a years-long investment in my Anki cards.

7 References

Allen, Mahler, and Estes. 1969. “Effects of Recall Tests on Long-Term Retention of Paired Associates.” Journal of Verbal Learning and Verbal Behavior.

Attygalle, Kljun, Quigley, et al. 2025. “Text-to-Image Generation for Vocabulary Learning Using the Keyword Method.” In Proceedings of the 30th International Conference on Intelligent User Interfaces. IUI ’25.

Cepeda, Coburn, Rohrer, et al. 2009. “Optimizing Distributed Practice: Theoretical Analysis and Practical Implications.” Experimental Psychology.

Karpicke. 2017. “Retrieval-Based Learning: A Decade of Progress.” In Learning and Memory: A Comprehensive Reference.

Karpicke, and Roediger. 2007. “Expanding Retrieval Practice Promotes Short-Term Retention, but Equally Spaced Retrieval Enhances Long-Term Retention.” Journal of Experimental Psychology: Learning, Memory, and Cognition.

———. 2008. “The Critical Importance of Retrieval for Learning.” Science.

Roediger, and Karpicke. 2006. “Test-Enhanced Learning: Taking Memory Tests Improves Long-Term Retention.” Psychological Science.

Su, Ye, Nie, et al. 2023. “Optimizing Spaced Repetition Schedule by Capturing the Dynamics of Memory.” IEEE Transactions on Knowledge and Data Engineering.

Ye, Su, and Cao. 2022. “A Stochastic Shortest Path Algorithm for Optimizing Spaced Repetition Scheduling.” In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. KDD ’22.