Nice! When I was building a spaced repetition toy a few years ago I took a different 'bottom-up' approach, where I dynamically fit the forgetting curve to the u

Nice! When I was building a spaced repetition toy a few years ago I took a different 'bottom-up' approach, where I dynamically fit the forgetting curve to the user's actual performance on any given card to come up with a unique memory half-life value for that card for that user, which was then used to schedule the next review at a given estimated recall % (typically 70-95% depending on whether the user wanted an "easy" or "hard" experience). As you need at least two data points to be able to fit the curve, you never have enough data to schedule the second review of a given card, so for this I used the average half-life accross the set of cards, or hard-coded values if it was the first item in the group. This way a set of cards (such as world flags) was always initially scheduled as though they were similarly difficult for the user, and then harder cards within the set would naturally be reviewed with a higher priority.