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

Failing grades soar as professors see greater AI usage, dwindling math skills in UC Berkeley computer science classes

dailycal.org

June 4, 2026

5 min read

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73/100

Summary

Failing grades in UC Berkeley's computer science classes reached 35.3% for CS 10 and 10.6% for CS 61A in spring 2026, significantly higher than previous semesters. Instructors attribute this increase to greater reliance on AI, insufficient mathematical preparedness, and understaffing.

Key Takeaways

The percentage of failing grades in UC Berkeley computer science classes rose significantly in spring 2026, with 35.3% of CS 10 students and 10.6% of CS 61A students receiving F's, compared to less than 10% in previous years.
Instructors attribute the increase in failing grades to students' reliance on AI, a lack of mathematical preparedness, and a rise in academic dishonesty.
Nearly 30 students in CS 10 were caught cheating on take-home exams in spring 2026, highlighting concerns about students' readiness for assessments.
Faculty members are advocating for the reinstatement of standardized testing for STEM admissions due to concerns about students' mathematical skills.

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Community Sentiment

Negative

Positives

Some users view LLMs as a powerful tool for learning, suggesting they can enhance understanding when used appropriately, rather than simply replacing critical thinking.
The discussion highlights a potential need for a societal adjustment in how we integrate AI into education, suggesting that future generations may adapt better to these tools.

Concerns

There are significant concerns about the cognitive decline in students and professionals who overly rely on LLMs, indicating a potential loss of essential skills like deep thinking and problem-solving.
The suggestion to ban generative AI for younger users reflects a fear that reliance on these tools could hinder the development of foundational skills in mathematics and coding.