Do Undergrads in MIT Struggle to Obtain Good Grades?
By
I teach 6.854 Advanced Algorithms every fall at MIT. This is a graduate class although about 1/2 the students are undergrads. The class assessments are based entirely on weekly homework and final project; there are no exams. Many of my problems are recycled from previous years because they are the most effective problems for teaching the material. As with most classes at MIT, collaboration is strongly encouraged (and, for most students, necessary to complete the work). I begin the first lecture with a discussion of what kind of collaboration is acceptable (working on solving the problems together) and what is not (copying anyone’s work, or any solutions you find online — you have to write up your own thoughts). I’ve also, in recent years, put an “ethics” problem on the first problem set, which lists various scenarios and asks which ones violate the collaboration policy and why. Students always get this question right. And, I say what I say in the previous paragraph. But it doesn’t help.
Just about every year, we discover (exactly) one cheating incident where a student finds solutions online and copies them. I suspect it’s the only one, because it’s honestly pretty easy to notice when the student solution is just like the one I wrote. In general, the student admits what they’ve done as soon as they’re confronted, expresses remorse, and explains that it’s just because they were under so much pressure and the course is really hard.
The students’ excuses, sadly, are true. I don’t condone this behavior, and we always send these students up before the office of student conduct. But I do understand this behavior: MIT is a place which prizes academic achievement above everything, and when you’re not achieving you feel tremendous pressure to do something about it. It’s a shame, because when you take away this pressure (I see this between semesters) the students turn into brilliant and enthusiastic people who just love learning for its own sake. I wish we could detach the learning that they all love from the assessment that they all hate, but nobody has solved that problem yet.
