I’m looking forward to finding one of these applications that uses a later generation version of the supermemo algorithm. SM2 is ok but the research that was put in to the later ones wasn’t bad. The detailed manner in which it was able to infer your individual learning profile and adapt repetition accordingly was also rather elegant. Of course, I could probably program it in to the Anki software myself if I was really interested.
FWIW, the main developer of Mnemosyne) (the SRS I’ve used for the past 2-3 years) is skeptical that SM3 and up really add anything compared to SM2. (See “Principles” and various emails by Peter to the mnemosyne-proj-users ML.)
That makes sense to me, since early on the time granularity is ‘one day’, leaving little room for adjustment and after a couple reviews pushes items out to 100s of days, shifting forward or back a few days doesn’t make much of a difference.
I would certainly expect diminishing returns. The key seems to be spaced repetition itself and the environmental conditions that our learning (and forgetting) mechanisms are adapted for can hardly be considered to be exquisitely precise.
I would have to look more closely at the existing studies and most likely perform more myself before I could establish just how much scope there is for optimising the repetition schedule by either individual or type of knowledge.
Wow. I am extremely tempted to download that and click ‘start’. I’ve been reading too much Harry Potter. What would make it worthwhile for me is if all the components maintained their deck structure and so could be easily removed in bulk if a couple of cards did not interest me.
You’re not supposed to choose by looking at the numbers, only decide if the fact was Hard / Good / Easy to remember.
Here is some information on the algorithm used by Anki, it’s modified from one of SuperMemo’s algorithms.
I’m looking forward to finding one of these applications that uses a later generation version of the supermemo algorithm. SM2 is ok but the research that was put in to the later ones wasn’t bad. The detailed manner in which it was able to infer your individual learning profile and adapt repetition accordingly was also rather elegant. Of course, I could probably program it in to the Anki software myself if I was really interested.
FWIW, the main developer of Mnemosyne) (the SRS I’ve used for the past 2-3 years) is skeptical that SM3 and up really add anything compared to SM2. (See “Principles” and various emails by Peter to the mnemosyne-proj-users ML.)
That makes sense to me, since early on the time granularity is ‘one day’, leaving little room for adjustment and after a couple reviews pushes items out to 100s of days, shifting forward or back a few days doesn’t make much of a difference.
I would certainly expect diminishing returns. The key seems to be spaced repetition itself and the environmental conditions that our learning (and forgetting) mechanisms are adapted for can hardly be considered to be exquisitely precise.
I would have to look more closely at the existing studies and most likely perform more myself before I could establish just how much scope there is for optimising the repetition schedule by either individual or type of knowledge.
If you are serious, you may find the Mnemosyne database torrent useful: http://www.reddit.com/r/cogsci/comments/9aufn/ever_wanted_to_analyze_860mb_of_spaced_repetition/
Wow. I am extremely tempted to download that and click ‘start’. I’ve been reading too much Harry Potter. What would make it worthwhile for me is if all the components maintained their deck structure and so could be easily removed in bulk if a couple of cards did not interest me.