It's Time to Stop Using Grades
Computational Complexity 2024-12-11
We use grades to evaluate students and motivate them to learn. That works as long as grades remain a reasonably good measure of how well the student understands the material in a class. But Goodhart's law, "When a measure becomes a target, it ceases to be a good measure," cannot escape even this most basic of academic measurements. Grades become irrelevant or even worse, counterproductive, as chasing grades may undermine a student's ability to master the material. So perhaps it is time to retire the measure.
Grading became a weaker measure due to grade inflation and academic dishonesty. Let's do a short dive into both of these areas.
The average grade has increased about a full grade level since I went to college in the '80s, and now more than half of all grades given are A's. As college tuition increased, students started thinking of college more transactionally, expecting more from their college experience while putting less effort into classes. Administrators put more weight on student course surveys for faculty evaluation, and the easiest way to improve scores is to give higher grades. And repeat.
If everyone gets an A, no one gets an A. It just becomes harder to distinguish the strong students from the merely good.
Academic dishonesty goes back to the beginning of academics but has advanced dramatically with technology. In my fraternity, we had filing cabinets full of old homework and exams ostensibly to use as study guides. However, if a professor reused questions from year to year, one could gain an unfair advantage.
With the growth of the Internet, Chegg, and more recently large-language models, those looking for an edge never had it so good. ChatGPT-4o1 can answer nearly any undergraduate exam question in any field—it even got an easy A when I tested it with one of my undergraduate theory of computing finals.
AI becomes like steroids: those who don't use it find themselves at a disadvantage. If a pretty good student sees their peers using LLMs, they'll start using them as well, initially just as a learning aid. But there's a very fine line between using AI as a study guide and using AI to give you the answers. Many fall down a slippery slope, and this starts to undermine the mastery that comes with tackling problems on your own.
We can try and counter all this by returning to harsher grading and more heavily weighting in-person, no-tech exams, but these approaches cause other problems. Already we see companies and graduate schools devalue grades and focus on projects and research instead.
So let's acknowledge this endgame and just eliminate grades, maybe keeping only Pass and Fail for those who don't even show up. The ones who want to master the material can focus on doing so. Others can concentrate on working on projects. Still others can earn their way to a degree with little effort but also with little reward.