Thanks, that looks great! ~60% probability I'll do my project on this, actually.
The second one actually looks more interesting and useful to me, since it would directly lead to improved scheduling. There's a lot of literature on the spacing effect, and it doesn't look like anyone's actually done empirical analysis of it on this scale before. (And I do a lot of reviews daily, so I wouldn't be surprised if this project actually took negative net time!) There's also disagreement between e.g. Supermemo and Anki about which algorithm is best, so the issue isn't very settled.
The first one (calculating brainpower for a day) seems easy to do to some extent - just look at the average time each review took, or some function of time-per-review and number of reviews. I'm doubtful about whether you could get more reliability out of looking at e.g. card ratings. Perhaps a better way to measure brainpower would be n-back, or Seth Roberts's arithmetic test.
There's also disagreement between e.g. Supermemo and Anki about which algorithm is best, so the issue isn't very settled.
Yes. Wozniak who wrote Supermemo did nearly all his work on his own. I think there a good chance that he missed significant things that are known in 2014 about machine learning in his work. Anki and Mnemosyne are also both written by people without strong knowledge of machine learning.
Maybe some deep learning algorithm is simply better than Wozniaks idea.
...The first one (calculating brainpower for a day) seems easy to do to some ext
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