2026-06-04站内改写3 min readUpdated: 2026-06-04

Failing grades soar with AI usage, dwindling math skills in Berkeley CS classes

At UC Berkeley, CS 10 and CS 61A had abnormally high failure rates in spring 2026, attributed by professors to increased AI usage and declining math skills. Students are over-relying on AI and underprepared, leading to calls for reinstating standardized tests and changes in teaching.

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According to Berkeleytime, 35.3% of CS 10 students and 10.6% of CS 61A students received F’s in spring 2026.

Hsi-Min Chan | Senior Staff

In addition, the guidelines state that “a typical GPA for a lower division course will fall in the range 2.8 – 3.3.” In spring 2026, both classes’ average grades were C-pluses, according to Berkeleytime, corresponding to a 2.3 GPA.

UC Berkeley teaching professor Dan Garcia taught both CS 10, “The Beauty and Joy of Computing,” and CS 61A, “The Structure and Interpretation of Computer Programs,” in spring 2026. Garcia believes the “primary driver” of these abnormally high failing rates is due to a “vast increase in academic dishonesty” due to students’ usage of large language models, such as Claude, ChatGPT and Google Gemini.

“Some of the numbers that you saw from the number of students who receive failing grades were because we caught them (cheating) and prosecuted them and are sending their cases to the center for student conduct,” Garcia said. “But in other cases, it’s students who are leaning a little too hard on LLMs to do their work for them, and then at exam time just really aren’t ready.”

According to Garcia, nearly 30 students in CS 10 were caught cheating on take-home exams in spring 2026.

Neither of Garcia’s classes this semester was graded on curves; instead, each letter grade has a point threshold. This means that students’ grades do not depend on their peers’ performances.

Garcia believes that instructors “should not be curving” but should instead make thresholds for each letter grade publicly available and give students many chances to reach them. He added that he loves the idea of “having no limit” to the number of A’s he gives students.

“I’m a strong, strong opponent of what Harvard is doing to say that only a fraction of students can earn A’s,” Garcia said. “I think you should have clear standards for what an A means, and then give tons of opportunity for people … to get to that A bar without lowering the standard. So everybody who’s curving is hiding that effect.  It’s completely hiding that effect, and it’s pretending as if nothing’s wrong, and something is definitely wrong.”

In addition to overreliance on AI, Garcia also pointed out that many students are underprepared mathematically, a concern echoed by campus associate teaching professor Gireeja Ranade.

Ranade noticed a similar lack of prerequisite mathematical skills in her spring 2026 EECS 127 class, “Optimization Models in Engineering,” which she described as “differently challenging” to teach this semester. The class saw a 16.8% F rate, far higher than the 5% of D’s and F’s that the EECS department describes as “typical” for an upper division course.

Ranade said students are expected to enter the course having taken classes on linear algebra, vector calculus and mathematical proofs. However, she found out in office hours that many students struggled with linear algebra, and was even more shocked when one student told her the linear algebra class they took at UC Berkeley had an “open-internet, open-AI policy” for homework and exams.

Both Garcia and Ranade have joined more than 1,300 UC faculty in signing a petition calling for the reinstatement of ACT and SAT standardized testing scores for STEM admissions in the UC system. The petition and its accompanying open letter detail similar concerns with students’ mathematical preparation.

Ranade also changed the structure of the course this year. Previously, EECS 127 included a final project completed with the guidance of the professor and a team of TAs. Due to a lack of staff, Ranade had to remove this portion of the class, on which she said most students get high scores.

According to a post on X by EECS department chair Jelani Nelson, the campus has had to reduce both undergraduate CS enrollment and the number of undergraduate TAs due to the high hourly wages that EECS TAs are paid.

Ranade and Garcia have both noticed the decline of student engagement in classes as well. Ranade said office hours used to be “overflowing,” but this semester, she and her TAs noticed “very low engagement” in office hours, despite frequently encouraging students to attend.

Garcia found a similar lack of attendance in his office hours over the past two semesters.

“I used to have full office hours, and for the first time, I was having nobody come to my office hours,” Garcia said. “It was just so surprising to sit in my office alone.”

Looking forward, both professors are rethinking their classes.

Garcia plans to “advertise” what happened in spring 2026 to his future classes on day one, while also trying to find a way to identify students who need extra remedial support.

Ranade emphasized that professors should be teaching students “more, not less,” in the age of AI, adding that she wants students to acquire critical thinking and analytical thinking skills necessary to become leaders to be “in a very competitive world.”

Both professors underscored the need for students to be more comfortable with difficult problems.

“We really need to make sure that we are preparing our students to be solid, contributing citizens and leaders — these are Berkeley students: not just next year or the year after, but for the next 40 years of their lives,” Ranade said. “We need to — and we want to — teach them how to … take on new challenges.”

“I love this phrase my colleague uses: ‘Confusion is the sweat of learning.’ I just love that,” Garcia said. “A lot of students, I think, are not putting in the sweat.”