Which is really a shame, as the spacing effect itself is such an underrated aspect of human learning that it almost feels like cheating.
Which is really a shame, as the spacing effect itself is such an underrated aspect of human learning that it almost feels like cheating.
It’s powerful, with a lot of depth to its features - but it’s also hideous, clunky and unintuitive, and it takes a long time to figure out how to use it effectively.
An HN-reading tech nerd can probably figure it out, but your average Duolingomaxxing normie? No chance.
Another example until recently was the extremely useful image occlusion enhanced add-on. Can you easily tell the difference between overlapping and nonoverlapping? At least they renamed those settings to the much more intuitive "Hide One , Reveal All" and "Hide All, Reveal One."
Second thing, control over workload should not be that hard. Anki requires too much tweaking to work reasonably.
Third thing, both old and new algorithm have a notion of "you are pressing the buttons wrong". If you are pressing the buttons wrong, you will end up with absurd intervals - like 4 months interval on something you just learned.
An SRS system which took more account of the human failings of the user might:
- let you pick a "max daily reviews" and then keep you from putting in too many new items up front, rather than letting you accidentally give yourself a huge daily workload after a few months
- let you tell it "I'm going to be on holiday in a month's time" and have it figure out what to do with reviews and new items to minimise disruption
- when you do come back after a break, pick the most useful reviews to offer the user up to the daily limit (e.g. something whose review interval is six months can wait a few more days, something the user added very recently and has seen only once could be put back into the "new items" bucket to relearn later, so if the user is only going to do 100 of their 300 due cards, other cards are more important to review today)
i really wish the UI would just hide number of cards due by default
Anki allows you to do that. It's in the deck preset options under deck limits. Nowadays you can also set weekday workloads, to reduce workload eg. during the weekend.
A human who had a lot of time to learn during January, because his job workload was easy is not failing anything if his job related workload becomes high in March and April. But, all that January effort will be punished by super high workloads in March and April in Anki.
Source: https://docs.ankiweb.net/deck-options.html?highlight=easy%20...
If you could set a study time of say 30 minutes, then when you skip a day, you could just do your usual 30 minutes and maybe only get through 50% of the scheduled cards, but you could slowly catch up over the next few days. And if on the contrary you run out of reviews for today, you could carry on with some scheduled for tomorrow until you've hit your target time.
FSRS can handle off-schedule reviews just fine, I think, so it should be able to accommodate such a rhythm where you don't always review cards on exactly the optimal day.
We seem to agree on the substance: that the SRS system should be able to work more humanely with and for the kind of entirely normal situations you describe, by for instance being able to adjust to variations in available time and picking the "best" cards to review rather than assuming the user will get through the whole lot, and in suggesting to them when they should do fewer new items to avoid difficulties in a month or two.
This reminds me of GTO (game theory optimal) play in poker.
There’s a perfect way to do things, so we should just try to do something as close to that as possible, right? The reality is that you can’t actually do things in this perfect way. In GTO’s case it’s that it’s too complex for a human to have memorized and in SRS many (not all) people will fail to follow the algorithm for one reason or another.
The problem is these strategies aren’t very resilient. If you miss the implementation by a bit, it can cause big losses. An algorithm that’s less theoretically optimal but more attainable by actual humans can end up much stronger in the real world.
The other reason I wrote my own system was to integrate SRS with extensive reading. Basically, my algorithm tracks the difficulty of all the words and grammar concepts, like FSRS; but then it gives you content at the right level for learning (either fewer than 5 new concepts, or an average of 95% known material).
And among the things that fits, it balances reviewing older material and learning newer material, based on what would have the largest impact. (Reviewing something you're about to forget has a bigger impact than learning something new, because the new thing you're going to forget much more quickly. So the balance of new / review and spaced repetition falls out naturally.)