Princeton tests device-free classrooms and new ways to assess student AI use

Princeton faculty are testing device-free classrooms and changing assessments as student use of AI grows. The university’s experiments range from paper-and-pencil seminars to oral defences and staged work that makes students show how they reached a final submission.

Watch Desk analysis

What happened

The Daily Princetonian reports that Princeton’s First-Year Seminars programme proposed an analog-classroom pilot this semester. In participating classes, laptops, tablets and phones are banned during class time in favour of paper and pencil. Four seminars are listed as part of the pilot.

The response is not one university-wide rule. In economics, students writing junior independent work or senior theses must submit AI-use disclosures and preserve prompt logs. The department has also added oral defences, in-person research activities and graded interim deliverables. Computer science faculty, meanwhile, are still gathering information about departmental policies and considering how assessment might change.

Why it matters

These are practical attempts to respond to AI use without pretending that a ban, a detector or a sternly worded policy settles the question. Students may be asked to document how they used generative AI, defend work in person, or demonstrate their understanding at several stages rather than only in the final product.

The trade-offs are visible too. Oral exams and close process checks may give instructors more insight into individual work, but the article notes that oral assessments can be difficult to run in large lectures. Princeton’s analog pilot will be assessed using end-of-semester student data and surveys, so its longer-term fate remains open.

Our read

The useful experiment is not simply putting laptops away. It is matching assessment to what a course is trying to teach, then checking whether the change helps. A device-free seminar may suit some teaching; it is not a ready-made answer for every class, particularly one with hundreds of students.

Princeton is trying several approaches at once, which makes the results worth watching. The university’s eventual evidence should help separate a policy that feels reassuring from one that actually improves learning.

What to watch

• What the end-of-semester surveys and data say about the analog-classroom pilot.
• Whether the First-Year Seminars programme expands the device-free option.
• How departments balance AI disclosure and oral assessment with the workload of large classes.
• What the computer science faculty committee recommends after its information-gathering phase.

Discussion spark: When students can use AI, should universities focus more on restricting devices in class or on assessing the steps behind the finished work?

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