A UC Berkeley study analyzed over 500,000 grades at a large, selective public research university in Texas and found that courses with high writing and coding assignments saw sharp grade increases since ChatGPT was launched. The share of A grades jumped by 13 percentage points, about 30 percent above the 2022 baseline, while average GPA rose by 0.12 points. The grade distribution narrowed, with A-minus and B-plus grades moving up to straight A's. The study tracks grade trends across eight fall semesters (2018 through 2025) in 319 courses spanning 84 departments. Each course's AI exposure is measured by its assignment mix from the fall 2022 syllabi, before ChatGPT existed. What matters most is the share of writing and coding tasks, the areas where AI performs best.
Homework grades are driving the spike, not exam scores. The research question is whether higher grades reflect actual learning gains or just AI doing the work. To find out, author Igor Chirikov also looked at how much homework counted toward the final grade. If AI really improved learning, grade increases should show up no matter whether a course leans on homework or proctored exams. But if AI is just replacing student work on unsupervised assignments, the effects should cluster in courses where homework carries more weight. That's what the data shows: In courses where homework counts for more than the median share of the grade, A's rise by an extra 16 percentage points compared to courses below the median with the same AI exposure. In those lower-homework courses, the effect is small and not statistically significant. The result is 'difficult to reconcile with broad learning gains or sorting effects alone,' Chirikov writes. Across all courses, the share of students earning at least an A or A-minus rises sharply after ChatGPT's November 2022 release, while shares at B-plus through C-minus barely move.
Grade inflation is nothing new at US universities. At Harvard, the share of A grades climbed from 24 percent in 2005 to 60.2 percent in 2025, the study notes. Earlier research pointed to teaching evaluations that reward leniency, competition between universities, and institutional grading policies. But AI works differently, Chirikov argues. Every earlier driver kicked in at the grading stage, after students had turned in their work. AI changes how the work itself gets made, before instructors ever lay eyes on it. If grades in writing- and coding-heavy courses increasingly reflect AI-generated output rather than real skills, employers and graduate programs could make worse selection decisions, the study warns. Chirikov also flags a feedback loop: If AI takes over skill-building tasks during college, graduates could end up weaker in exactly the areas where AI is strongest. That could speed up automation and widen skill gaps in the job market.
Source: thedecoder
