University Professor Stops Grading For Correctness As Students Turn To AI For Answers

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A prominent university mathematics professor has stopped grading student assignments for correctness, arguing there is "no point" in awarding marks when AI tools can generate solutions within seconds

Richard Borcherds, a British mathematician and Fields Medal laureate teaching at the University of California, Berkeley, explained that traditional assessment methods have become counterproductive in the age of generative models like ChatGPT.

He argued that rewarding technical correctness could disadvantage students who complete their work honestly while giving others an incentive to use AI to produce their answers.

"Grading for correctness just adds a huge incentive for them to use AI for homework instead of doing it themselves, and penalises students for honesty," Borcherds told the NY Post.

Borcherds said the widespread AI use has made it increasingly difficult to distinguish students' own work from AI-generated answers

Speaking to the university's campus paper, The Daily Californian, Borcherds added that hiring teaching assistants to scrutinise routine assignments had become a poor use of university resources.

Rather than grading problem sets based on the accuracy of students' solutions, Borcherds has adopted a binary grading system that awards credit based on whether students submit their coursework on time.

The situation highlights the challenges universities face in assessing student work as AI tools become more capable

Borcherds acknowledged that he was unsure how educators should respond to the changes, even turning to the technology itself for advice.

"I have no idea what to advise. I even asked ChatGPT this exact question, and even ChatGPT said it didn't have any idea what was going to happen," he remarked.

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