I still believe that the spaced repetition dataset produced by memosyne is underanalysed. Gwern put effort into bringing that dataset into a good format.
In particular:
Is there a way to calculate the brain power for an individual day? Reviews made at a high brainpower day would have a higher successful. Having such a metric would be very useful for Quantified Self (QS) purposes because it means that everybody who uses Anki or memosyne daily would get a free QS metric.
Is there a better way to to calculate the interval for cards than the supermemo algorithm that can be proven to be better based on the data from the memosyne set? If so how much better? (If you find something that shows real improvement over the status quo, the next step would be to write an Anki addon that does AB split testing with it)
I think that especially the first task has the chance to provide a decently cited academic paper.
I don't know how much effort either of those tasks takes and whether it would go beyond a project for a college course, but both projects should be interesting and highly useful. You might also find other interesting question when you investigate the data set.
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...
If it's worth saying, but not worth its own post (even in Discussion), then it goes here.
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