3/19/2023 0 Comments Ankiapp suggestion![]() ![]() Trying to jam more and more things into your head in the same period of time will have diminishing returns, and at some point likely have adverse effects. ![]() With this change, do you think the twins will still have the identical retention rates? As an experiment, one twin changes their new cards per day to 30, while the other twin changes theirs to 10. Both twins have identical settings, and have near-identical retention rates. Consider the following:Ī pair of identical twins are using Anki to learn French. These three metrics provide useful information that you would have otherwise missed had you only looked at true retention. In fact, if you looked at true retention alone, you’d be missing some crucial elements:įortunately, these statistics are built in to Anki, so there’s no need to install any addons. However, this isn’t the only useful metric. While all three are useful, I personally prefer True Retention by Card Maturity. True Retention by Card Maturity Simplified.There’s actually a few options you have to pick from: True retention doesn’t come with Anki by default, you’ll have to install the addon. The generally agreed upon metric (and what we’ll also be using) is true retention. In order to improve the effectiveness of Anki, we first need some sort of way to define and measure “effectiveness”. For that reason, it’s useful to take matters into your own hands - examine your own learning statistics, and slowly make tweaks over time. Given that there’s so much variance of things to be learned, it’s hard to expect a single algorithm to be equally effective for all of them. There’s even a significant difference between learning new vocabulary in your native language and your target language. For example, learning new vocabulary is much different than learning mathematical formulae. One major difficulty in designing a good algorithm is the sheer breadth of things that can be learned. Trying to reduce that work will obviously show effects in your retention.įurthermore, SRS algorithms historically haven’t been particularly scientific anyways, so it’s hard to say for sure that a newer implementation will definitely be better than its predecessor. No matter what, you have to put in serious effort to reach proficiency in something. However, it actually makes a bit of sense. This result may come as a surprise to those assuming that decades of research and algorithm refinement should have resulted in something far superior to SM-2. Supermemo showed that while the total number of reps and review time was lower for SuperMemo, so was the the accuracy.įor those that are too lazy to click on the actual article, the average accuracy for Anki was 91.8%, while SuperMemo was 65.7%. A comparison in Battle of the Spaced Repetition Heavyweights: Anki vs. That said, newer isn’t necessarily better. The reason for such a gap is because the SM-2 algorithm is publicly available, while the newer versions aren’t. SuperMemo on the other hand has been continuing to update their algorithm, and as of 2019 they are on SM-18. Anki uses the SM-2 algorithm, which was created for SuperMemo in the 1980s. This is (sort of) for good reason.įor starters, there’s not nearly enough research on the subject of spaced repetition, especially when it comes to the algorithm itself. However, it’s no secret that Anki is pretty un-optimal out of the box. SRS is one of the most powerful learning tools we have available to us. Updated A Discussion of the Anki Algorithm ![]()
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