Month: April 2019

This post concludes the series of posts on Anki and follows the post
introducing Anki and another one about the theory behind Anki.

I have been using Anki for five years and achieved high consistency in completing daily reviews. Here are my best practices:

1. Be selective about cards you create in Anki: My goal is to learn the information on my Anki cards for a very long time, possibly for life.
2. Do not import cards created by others: A big part of Anki is the mental connection to the cards you create because you invest time in their creation.
3. Make cards atomic: When cards contain too much information it is likely you will have problems remembering the cards. Anki tracks the history of your answers and flags the cards that you repeatedly answer incorrectly as leeches. Anki removes these cards from reviewed cards and they become suspended.
4. Do not give in to leeches: Decide whether you still wish to remember the information on a leech (see point 1 above). If you do, make it easier to remember, possibly by rewriting the card, so it is more atomic using cloze deletion.
5. Spend time maintaining your Anki database: As you review cards, mark the ones that have issues, like cards containing misspelled words or confusing format. Review the marked cards at least weekly to correct them.
6. Vary the environment where you study: Anki has applications for computers (Windows, MacOS, Linux) and mobile devices (iOS, Android), making it easy to review them anywhere. The more diverse environments you use to study, the easier it is to recall the information from them in real life where you need them. Anki synchronizes your notes between your devices, so do not worry about losing your progress.
7. If you want to explore more suggestions, there is quite a famous list of 20 rules for effective learning. The list is written for SuperMemo, a product similar to Anki, but the rules are generic and apply to Anki as well.

It is easy to modify and extend the Anki’s functionality using add-ons written in Python. You can view a list of all available add-ons here. The following is a list of add-ons that I use:

• AutoDefine: Automatically retrieves the definition of an English word from the Merriam-Webster dictionary and populates the Anki card, optionally offering to include a corresponding image retrieved from Google. To learn how to use this add-on, please watch this tutorial. The author of this add-on is my son, who introduced me to Anki years ago.
• Syntax Highlighting for Code: Inserts syntax-highlighted code snippets into your notes. Syntax of many programming languages is supported.
• Hierarchical Tags: Using tags in Anki allows users to divide notes according to topics they belong to. Install this add-on to improve the usage of tags.

Anki is a wonderful tool that you can use to reap the benefits of the best memory augmenting techniques available. However, it is not the most user-friendly software. One of the areas that could be improved on is configuring Anki. There are many complicated manual settings that users can set to modify the default functionality of Anki. These manual settings could be replaced by a machine learning algorithm based on a previous history of how the user answered the questions.

In closing, I hope that this series was useful to you. If you have any comments or questions about Anki, please write them in the comment field below. You can also search the manual or visit the vibrant Reddit community. Happy learning!

This post covers the theory behind Anki and follows the previous post introducing Anki. The last post in this series describes best practices for using Anki.

One of the best meta-analyses reviewing best approaches to learning is Improving Students’ Learning With Effective Learning Techniques by Dunlosky et al. If I were to summarize its 50+ pages in one paragraph, it would be: The most utility for improved learning is provided by distributed practice and practice testing, followed by interleaved practice, elaborative interrogation, and self-explanation. In contrast, popular techniques such as highlighting and rereading provide only low utility for learning. The meta-analysis was done in the context of students’ learning, but the top techniques were shown to benefit learners across varying ages and abilities. This makes these techniques applicable to lifetime learning.

Anki implements the above mentioned top two techniques directly and provides a way for the third most useful practice. Let’s examine these three techniques in more detail:

• practice testing (a.k.a. active recall): memory needs to be actively stimulated during the learning process, which is what Anki does by showing questions that the user must answer.
• distributed practice (a.k.a. spaced learning): learning is broken up into several short sessions over a long time. Anki schedules flashcards for review based on an algorithm over a long period.
• interleaved practice: mixing multiple subjects or topics while studying improves learning. Anki cards are organized in decks and Anki encourages users to limit the number of decks being reviewed. Since decks are reviewed in succession, ideally all the Anki cards are within a single deck to ensure that knowledge from different subjects is reviewed at the same time.
  

Another great source of the theory behind Anki is a lengthy article by Michael Nielsen titled “Augmenting Long-Term Memory,” where the author lists many historical underpinnings for memory augmentation. It is surprising that as early as in 1885, some scientists studied memory decay, see “Memory: A Contribution to Experimental Psychology” by Hermann Ebbinghaus. For a modern take on memory decay, read “A Trainable Spaced Repetition Model for Language Learning” that describes an algorithm used in Duolingo, an excellent app for learning foreign languages.

At the end of his article, Michael Nielsen goes through a rough estimate of the effort needed to remember one piece of information. It assumes that the user takes just a few seconds to recall a fact listed on an Anki card when it is scheduled. If her effort is spaced over twenty years in ever increasing intervals, the total time spent on the card is about 5 minutes. This sounds like a decent trade-off: spending a total of 5 minutes over twenty years will result in remembering one particular flash card. In other words, it will take an average of only 7 minutes daily to remember 10,000 flashcards for twenty years!

This is the first article in a series of posts about Anki, a spaced learning system to improve users’ long term memory. The next article in this series will cover the theoretical background of spaced learning, and the final article will concentrate on best practices using Anki.

I have been using Anki software for years to learn information that is important for me to remember for a long time. Such information can be defined very broadly and can include almost anything, from a penny test to random forest and The Starry Night.

I have almost ten thousand individual pieces of information in Anki and review them daily in about half an hour. I often hear comments like “There is no way you can review this amount of information daily!”, so let me explain.

Anki is a system to store flashcards, where individual cards are scheduled for review at various intervals determined by an algorithm. The user reads a question on one side of the flash card and answers to herself. She then compares her answer to the correct answer displayed on the back of the card. If she answers the card correctly, the card will be offered for review in ever-increasing intervals. If she misses the question, the card is scheduled the next day to restart the learning cycle. Cards that the user has answered correctly many times are called mature cards and can be scheduled again after a year or more. Because each day the user reviews just a subset of the information contained on all her flashcards, all scheduled cards can be reviewed daily in 30 minutes or so.

Let’s look at how one card might look. Let’s assume I want to remember how The Starry Night painting by Vincent van Gogh looks. Here are screenshots of both sides of the card.

Similar questions can be created to inquire about the painter and the title of the painting. Indeed, questions can be created about anything.

To recap what I covered today. If you want to remember something, no longer do you need to rely just on your memory. You can selectively choose what to remember. For a modest investment of 30 minutes or so daily, you can remember it for decades.