https://www.duolingo.com/Susanna35

Would this be feasible?

When we make a mistake, we always get extra exercises. I'd like to see it set up so that you would be sure to get every mistaken exercise repeated. Repeating the exercise while it is still somewhat fresh in one's mind should make it "stick" a little better. I don't know what kind of algorithm for selecting questions you would use - I know nothing about the programming languages and functions you use, and it may not be practical to do it. But if it could be done, I think we would learn some things more quickly, and not repeat the same mistakes as much.

October 22, 2015

4 Comments


https://www.duolingo.com/Garrett2015

A great idea. Memrise does this, and allows you the chance to type in the corrected version. It seems to help the learning process. Plus, having the chance to correct your mistakes is also a more encouraging experience, I think.

October 22, 2015

https://www.duolingo.com/ariadna.m

Yes, I also use Memrise to help with this. Since I've started using it my language learning has progressed a lot faster. I also think Duo staff should implement it. :)

October 22, 2015

https://www.duolingo.com/underwood.jones

When we had the "heart" life bar, I was in the A/B test that had the "Correct your mistake" feature built in so you only lost half of a heart. My husband was not as fortunate and really wanted to be in my test group because he was doing the "old" German tree which was quite difficult and impractical in its layout. Since they've redone how exercises work they haven't implemented any similar features, but I second your request for one. I think it would be very feasible and practical.

October 23, 2015

https://www.duolingo.com/Susanna35

It appears that this is happening right now, at least in the Italian. I have been refreshing my Italian trees for the last couple weeks or so, and just recently, it seems that every exercise that I miss is repeated somewhere during the lesson. If this is on purpose, and not accidental, thanks a lot, Duo team!

November 5, 2015
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