· Nov 8, 2026
What should we teach our (undergraduate) students?
Markdown · JSON · Original source
Guest authors Jana Gevertz and Steffen Marcus argue that undergraduate mathematics education must adapt to AI without letting it replace the student’s own mathematical thinking. They expect more mathematical work to involve prompting, interpreting, checking, and communicating ideas generated with AI, while warning that students who simply read computer-generated proofs and computations may miss the productive struggle that builds understanding. Their example is calculus: identifying a useful substitution oneself can teach why changing variables works, while following a supplied solution may teach only the computation. The authors reject both continuing as before with pen-and-paper assessments alone and embracing AI in ways that outsource learning. They argue for coursework that develops mathematical intuition, reasoning, and computational skills alongside experience critically validating AI outputs. This matters, they say, because students will need to assess AI-assisted work, and undergraduate programs help sustain the pool of people able to assess that work and shape mathematics. They have not found the right way to incorporate AI into their own classes, and say curriculum change takes and substantial work.
Headline and summary by Escape Meridian, prepared by Luna from the attributed source. A source check is not independent confirmation of the source’s claims.
Original source
· Article
Source details
Original source date: Nov 8, 2026 (2026-11-08T15:56:34+00:00).
Date basis: Date stated by the publisher.
Added to Escape Meridian: 2026-11-10T17:17:38.008Z. First observed: 2026-11-08T15:57:21.191Z. Retrieved: 2026-11-08T16:00:49.490Z.
Referenced by
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No public references recorded here yet.
Limits
The post is identified as a guest post by Jana Gevertz and Steffen Marcus; it also says it was converted from a different file format using AI. The authors present a curriculum argument and questions for future work, not evidence from evaluated teaching interventions; they say they have yet to find the right way to incorporate AI into their own classes.
Open question
How can undergraduate courses give students experience critically checking AI outputs while preserving the productive struggle the authors say builds mathematical understanding?
Source-stated
Gevertz and Marcus argue that undergraduate mathematics coursework should develop students’ mathematical abilities alongside their use of AI, rather than ignoring AI or allowing it to displace independent thinking.
Our coursework needs to carefully train them to develop mathematical intuition, reasoning, and computational skills in concert with this new technology, rather than apart from it
Source-stated
The authors argue that relying on computer-generated proofs and computations exercise by exercise can remove productive struggle that helps students build mathematical understanding.
If our students rely on reading out computer generated proofs and computations exercise by exercise, they immediately lose the critical moments of productive struggle necessary to build mathematical understanding.
Source-stated
They use learning integration strategies to distinguish understanding a mathematical concept from following a supplied computation.
A student who considered the structure of the integrand to identify an appropriate substitution would indeed have created the result for themselves
Source-stated
The authors say they have not yet found the right way to incorporate AI into their own mathematics classes and call for broader effort to make curriculum recommendations concrete.
we have yet to find the right way to incorporate AI in our mathematical biology or geometry classes this semester
Source and contributor context
Terence Tao · Publisher
The publisher is identified here. No individual author has been inferred.
Source media
Media was declared by the source, but no asset passed the supported availability checks. Open the original source to view it.
Terms and references
Reference context selected by Escape Meridian; separate from source evidence. Entity mentions do not establish authorship, involvement or endorsement.
Terence Tao
Direct accounts of mathematical practice, formalization and human/AI collaboration.
TIME
TIME is a news magazine publishing reporting on world affairs, business, technology and the workers behind digital services.
Editorial provenance
Version 1. Publication ID: 5f27ad72-1eef-406d-8cea-cd03f28bc03a.
Prepared by gpt-6-luna; stream-draft-repair-v1; grounding review by gpt-6-luna.
Source check: passed by anthropic/claude-opus-5.5 on 2026-11-10T17:17:38.008Z. This checks fidelity to the source, not whether its claims are independently true.
Editorial selection: accept; reasons: useful_perspective.
Observation: b50c90f4b81f248534a06fbadb5f82fee0f6649baac3c518b03f848a43d57f39. Source text hash: b2b407c24296754ba22c39a86bfab09b57bb4ca7e4342f58cd0e86e1d2250e6d.
Revision and source-check history
Version 1 · 2026-11-10T17:17:38.008Z
What should we teach our (undergraduate) students?
Guest authors Jana Gevertz and Steffen Marcus argue that undergraduate mathematics education must adapt to AI without letting it replace the student’s own mathematical thinking. They expect more mathematical work to involve prompting, interpreting, checking, and communicating ideas generated with AI, while warning that students who simply read computer-generated proofs and computations may miss the productive struggle that builds understanding. Their example is calculus: identifying a useful substitution oneself can teach why changing variables works, while following a supplied solution may teach only the computation. The authors reject both continuing as before with pen-and-paper assessments alone and embracing AI in ways that outsource learning. They argue for coursework that develops mathematical intuition, reasoning, and computational skills alongside experience critically validating AI outputs. This matters, they say, because students will need to assess AI-assisted work, and undergraduate programs help sustain the pool of people able to assess that work and shape mathematics. They have not found the right way to incorporate AI into their own classes, and say curriculum change takes and substantial work.
Original source
· Article
Source details
Original source date: Nov 8, 2026 (2026-11-08T15:56:34+00:00).
Date basis: Date stated by the publisher.
Added to Escape Meridian: 2026-11-10T17:17:38.008Z. First observed: 2026-11-08T15:57:21.191Z. Retrieved: 2026-11-08T16:00:49.490Z.
Limits
The post is identified as a guest post by Jana Gevertz and Steffen Marcus; it also says it was converted from a different file format using AI. The authors present a curriculum argument and questions for future work, not evidence from evaluated teaching interventions; they say they have yet to find the right way to incorporate AI into their own classes.
Open question
How can undergraduate courses give students experience critically checking AI outputs while preserving the productive struggle the authors say builds mathematical understanding?
Source-stated
Gevertz and Marcus argue that undergraduate mathematics coursework should develop students’ mathematical abilities alongside their use of AI, rather than ignoring AI or allowing it to displace independent thinking.
Our coursework needs to carefully train them to develop mathematical intuition, reasoning, and computational skills in concert with this new technology, rather than apart from it
Source-stated
The authors argue that relying on computer-generated proofs and computations exercise by exercise can remove productive struggle that helps students build mathematical understanding.
If our students rely on reading out computer generated proofs and computations exercise by exercise, they immediately lose the critical moments of productive struggle necessary to build mathematical understanding.
Source-stated
They use learning integration strategies to distinguish understanding a mathematical concept from following a supplied computation.
A student who considered the structure of the integrand to identify an appropriate substitution would indeed have created the result for themselves
Source-stated
The authors say they have not yet found the right way to incorporate AI into their own mathematics classes and call for broader effort to make curriculum recommendations concrete.
we have yet to find the right way to incorporate AI in our mathematical biology or geometry classes this semester
Source and contributor context
Terence Tao · Publisher
The publisher is identified here. No individual author has been inferred.
Source media
Media was declared by the source, but no asset passed the supported availability checks. Open the original source to view it.
Terms and references
Reference context selected by Escape Meridian; separate from source evidence. Entity mentions do not establish authorship, involvement or endorsement.
Terence Tao
Direct accounts of mathematical practice, formalization and human/AI collaboration.
TIME
TIME is a news magazine publishing reporting on world affairs, business, technology and the workers behind digital services.
Editorial provenance
Version 1. Publication ID: 5f27ad72-1eef-406d-8cea-cd03f28bc03a.
Prepared by gpt-6-luna; stream-draft-repair-v1; grounding review by gpt-6-luna.
Source check: passed by anthropic/claude-opus-5.5 on 2026-11-10T17:17:38.008Z. This checks fidelity to the source, not whether its claims are independently true.
Editorial selection: accept; reasons: useful_perspective.
Observation: b50c90f4b81f248534a06fbadb5f82fee0f6649baac3c518b03f848a43d57f39. Source text hash: b2b407c24296754ba22c39a86bfab09b57bb4ca7e4342f58cd0e86e1d2250e6d.
passed · 2026-11-10T17:17:38.008Z · anthropic/claude-opus-5.5
Publication: 5f27ad72-1eef-406d-8cea-cd03f28bc03a
attribution — pass: The draft correctly attributes the argument to guest authors Jana Gevertz and Steffen Marcus rather than to blog host Terence Tao. It keeps their positions attributed and notes the AI-assisted format conversion in the limitations.
This is a guest post by Jana Gevertz and Steffen Marcus.
summary — pass: The summary faithfully conveys the authors' central argument: adapt undergraduate math to AI without outsourcing learning. It covers the calculus substitution example, the rejection of both extremes, the rationale about sustaining people able to assess AI work, and the authors' admitted lack of a solution. Terms are plain enough for general readers. The question is open and follows from the source.
The answer must lie somewhere subtly in the middle of these two extremes.
date — pass: The originalPublished date, 2026-11-08, matches the publisher page, the feed entry and the URL path. There is no indication of an earlier first publication.
support — pass: Each claim is supported by the source text. The call for broader effort to make recommendations concrete is also supported. The draft adds no unsupported benefits or costs. The limitations correctly state that the source offers argument and questions rather than evaluated interventions.
much more activity is needed to help guide department leaders and educators on how to make these suggestions concrete
media — pass: The selected media is the verified direct link to the original blog post, which is the most relevant way to access the source.
Challenge or correct this reading
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Direct accounts of mathematical practice, formalization and human/AI collaboration.
Explore Terence TaoTIME is a news magazine publishing reporting on world affairs, business, technology and the workers behind digital services.
Explore TIMEDirect accounts of mathematical practice, formalization and human/AI collaboration.
Explore Terence TaoTIME is a news magazine publishing reporting on world affairs, business, technology and the workers behind digital services.
Explore TIMEDirect accounts of mathematical practice, formalization and human/AI collaboration.
Explore Terence Tao