From undergraduates to Ph.D.s, how is AI shifting classroom policies?

From undergraduates to Ph.D.s, how is AI shifting classroom policies?

From undergraduates to Ph.D.s, how is AI shifting classroom policies?

https://stanforddaily.com/2026/03/07/a-new-wave-of-education-from-undergraduates-to-ph-d-s-how-is-ai-shifting-classroom-policies/

Publish Date: 2026-03-07 17:08:00

Source Domain: stanforddaily.com

  • Rapid AI Growth: University professors are adapting curricula to address the ethical use of AI while also providing essential learning tools in a world where AI is becoming increasingly incorporated into everyday life.

  • AI Usage Surge: Over 90% of university students globally use AI for educational aid, with AI use tripling since 2024 according to a Copyleaks survey.

  • Curriculum Modifications: The computer science department at Stanford University, led by Professor Chris Gregg, is altering syllabi to promote hands-on learning and in-person assessments, stressing foundational skills over AI use.

  • In-Person Assessments: New strategies involve in-person assessments in CS106B courses, where teaching assistants provide individualized feedback, fostering deeper comprehension and reducing reliance on AI in learning.

  • Regulation in Humanities: Humanities departments are strict about AI use, aiming to develop students’ distinctive abilities in writing, reading, and research, reinforcing the importance of human touch in these skills.

  • Stanford Initiatives: New programs like AI Meets Education at Stanford (AIMES) are guiding professors and students on ethical AI use, and the Office of Community Standards is working on policy changes regarding AI’s academic misuse.

  • Adaptation Based on Course Level: While undergraduate courses have strict AI policies, advanced courses and graduate programs often allow more AI usage, reflecting the different educational needs and students’ abilities.

  • Research Opportunities with AI: Graduate students are increasingly integrating AI into their research, pushing the boundaries of knowledge, but also raising questions about appropriate AI use in academia.