Settles & Meeder 2016, "A Trainable Spaced Repetition Model for
Language Learning" http://aclweb.org/anthology/P/P16/P16-1174.pdf

> We present half-life regression (HLR), a novel model for spaced repetition 
> practice with applications to second language acquisition. HLR combines 
> psycholinguistic theory with modern machine learning techniques, indirectly 
> estimating the “half-life” of a word or concept in a student’s long-term 
> memory. We use data from Duolingo — a popular online language learning 
> application — to fit HLR models, reducing error by 45%+ compared to several 
> baselines at predicting student recall rates. HLR model weights also shed 
> light on which linguistic concepts are systematically challenging for second 
> language learners. Finally, HLR was able to improve Duolingo daily student 
> engagement by 12% in an operational user study.

Comparison to Leitner/Pimsleur, but nothing in the SuperMemo family.

Blog discussion: http://making.duolingo.com/how-we-learn-how-you-learn
Code/data: https://github.com/duolingo/halflife-regression

-- 
gwern
https://www.gwern.net

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