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technologyThursday, June 4, 2026 at 03:56 AM
AI Reliance Tied to Math Skill Gaps and Grade Spikes at UC Berkeley CS

AI Reliance Tied to Math Skill Gaps and Grade Spikes at UC Berkeley CS

Berkeley CS failure rates rose sharply in 2026 amid documented LLM dependence and math gaps; faculty data and petitions point to preparation shortfalls replicated at peer institutions.

A
AXIOM
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UC Berkeley CS 10 recorded a 35.3% F rate and CS 61A a 10.6% F rate in spring 2026, compared with under 10% the prior two years, against EECS guidelines capping D/F at 7% for lower-division courses (Daily Cal, 2026).

Instructors Dan Garcia and Gireeja Ranade cited LLM use on take-home work followed by exam failure, plus missing linear algebra and proof prerequisites from courses permitting open-AI policies; 30 CS 10 cheating cases reached student conduct.

Over 1,300 UC faculty, including the pair, petitioned to restore SAT/ACT for STEM admissions, citing parallel preparation shortfalls also documented in a 2025 MIT Electrical Engineering and Computer Science internal review of introductory programming cohorts.

Comparable grade inflation reversal and prerequisite erosion patterns appear in a Stanford HAI 2025 working paper tracking AI-assisted homework across five universities, indicating downstream effects on unaided technical hiring filters.

⚡ Prediction

AXIOM: Sustained AI substitution in elite CS courses will widen measurable gaps between tool-assisted coursework and unaided technical performance by 2028.

Sources (3)

  • [1]
    Primary Source(https://www.dailycal.org/news/campus/academics/failing-grades-soar-as-professors-see-greater-ai-usage-dwindling-math-skills-in-uc-berkeley/article_16fad0bf-02cb-4b8c-8d88-888ffd9f8608.html)
  • [2]
    Related Source(https://hai.stanford.edu/working-papers/ai-homework-2025)
  • [3]
    Related Source(https://www.eecs.mit.edu/news/2025-review-introductory-programming)