Wednesday, December 14, 2011

Grading

Some folks at the NSDI meeting were nice enough to say that it was nice that I was blogging again.  Sadly, I've been under-the-gun busy for the last several weeks, but it was a reminder that I should be getting back to this now and again.

One thing that's taken my time the last week is grading.  I was teaching my graduate course this semester, on randomized algorithms and probabilistic analysis, using my book as the base.  Unfortunately, I teach this course at most every other year, which means it's hard if not impossible to find a suitable TA.  (As for my own students, Zhenming is on an internship this semester;  Justin's on fellowship and essentially required not to TA.  Also, both have been extremely busy this semester doing really great work, so why would I want them to TA instead of doing their research now anyway?)  So this year I didn't have one.  Which means I graded things myself.

It's been a while since I've graded a whole course.  I do grade exams (with the TAs) and one full assignment (myself) every year in my undergraduate class.  But grading every week is really at least as bad as having to do homework every week.  I'd say worse;  very little interesting thinking involved, just a lot of reading, checking, and moving papers or files around in a time-consuming fashion.  Somehow, though, I don't think the students sympathize.  

I think I remember one graduate class in Berkeley where a student (or maybe a group of students) were required to take on the grading every assignment.  I like that plan.  In fact, right now I like any plan that doesn't involve me grading the next time I teach this class.  One plan is of course no/minimal homework, or homework without grades.  However, I do believe students learn by doing homework, and I've found that in most circumstances a grade is the motivator that makes them get the homework done, so I'll have to find a plan that involves grading somehow.         

3 comments:

azotlichid said...

You can do what David Karger does for Advanced Algorithms. Make 10% of the grade reward "service", which usually consists of grading one problem. Estimate your class size and then plan homework assignments accordingly, so that each individual student wouldn't have to grade too many times.

Jeffe said...

I think I remember one graduate class in Berkeley where a student (or maybe a group of students) were required to take on the grading every assignment

That would be Dick Karp's CS 277; I took that class, too. I learned almost as much from grading the homework as I did from solving it.

Anonymous said...

I love how your frustration comes out in this post.

Other successfully tried strategies include teaching so poorly that most students drop or making the problems so difficult that most do not try or drop.