Partial Credit

One the the benefits of ASSITments is that you can learn from more than just looking at Boolean correctness on your posttest to a more nuanced view.

The ASSISTments team has done a lot of work showing that this gives you more value. In 2009 we published we can better predict their state test scores if we take into account the number of attempts and the number of hints they take compared to a "Boolean correctness only" attitude.
In 2013 we used partial credit per question to better predict the next question in assistments.  For instance, in a boolean correctness world, a kid that makes a wrong attempt (as their first action) versus a kid that asks for a hint will both be marked wrong.  A boolean correctness way of looking at the world will treat these two kids the same.  Furthermore, the kid that made a wrong attempt but then on the 2nd action got the problem correct is a very different student than a student that make 4 more guesses and then asked for every hint.  The paper below shows that we can use this intuition to better predict their performance on the next question. 
Others in my team have used this extra information to make further improvements.
A down side of the above work is we were just predict performance on the next question but can we use this info to better predict something later?  In the below paper also used these extra information to predict a test 6 months later
We have also shown that you can use response times as a useful predict of student performance.
So we encourage you, the researcher, to use this extra information to get a more nuanced look at student performance.  

Of course we are not the only to do this, or even the first.  Even researchers at the venerable Education Testing Service have know for a long time that they can get a more sensitive measure of student if we do this, but ETS is a testing company not meant to help student learn, so they don't bother.  See the above papers for many other references to literature for others that have been doing partial credit for a long time.