I’m not sure, but I thought their business model involved applying machine learning on user answers, like their translations of excerpts of written text / handwriting samples.
I think what I was recalling is the crowdsourcing translations mechanic, which is far more low tech:
> But wait – how could a beginner-level student translate advanced sentences? The solution that Duolingo employs uses the power of crowdsourcing, which involves many students offering their attempts at translating individual sentences. As each student submits a sentence, they can rate others’ translations, and the most highly rated translations “rise to the top.”
Over time, entire documents are translated and students gain many skill points for their language practice. It’s easy to see how the data collected from users could be useful to improve the algorithms that underly computer translation[…]
Duolingo has come a long way from those origins. It’s a gamified language learning app now, but with support of some languages reflecting that earlier crowd-sourced era. This video is a super interesting dive into the history and current state:
FWIW, I like Duolingo and think it is a healthy and productive use of gamification, but that does come at the cost of pure efficiency and comprehensive treatment of grammar. It’s best when paired with other tools.
Most people’s problem with learning a language is not speed, it’s the quit rate.
