Redesign an assignment for the AI era

No take-home assignment is AI-proof, and AI-text detectors are unreliable enough that they should not be the basis for accusing a student. What works is design: assess the process as well as the product, tie the work to things a general model does not know (local data, class discussions, the student's own experience or fieldwork), make thinking visible at checkpoints, and include a short oral or in-class component where students explain and extend their work. Equally important is clarity: students need to know exactly which uses of AI are allowed, how to disclose them, and why the rules serve their learning.

Redesign this assignment with the AI stance
def:ai_stance.

1. Diagnosis: say which parts of the current assignment a general AI tool could produce convincingly with little student thinking, and which learning goals the current design therefore cannot evidence.
2. Redesigned assignment: rewrite the student-facing brief. Keep the learning goals and roughly the same workload. Use the strategies that fit the goals best, typically several of:

• grounding in specific, local or class-generated material (data the class collected, a local issue, an in-class discussion, a text annotated in class);
• personal connection or reflection that is part of the learning, not decoration;
• visible process: proposals, notes, drafts, version history or annotated decisions;
• in-class components under normal conditions for the part that most needs to be the student's own;
• a product that requires judgement about sources or outputs, not just generation.

1. Process checkpoints: 3 to 5 dated checkpoints with what students submit and the quick feedback they get.
2. Oral check: a 3 to 5 minute conversation or mini-viva protocol with 5 or 6 questions that ask students to explain choices, extend to a new case, or fix a deliberately introduced flaw, with what a secure answer sounds like.
3. AI-use policy for students fitted to the stance:

• banned: what counts as AI use, why it is excluded for this task, and which tools remain fine (spell check, for example);
• allowed-with-disclosure: permitted uses (brainstorming, feedback on a draft, explaining a concept) and not permitted uses (generating the submitted text or answers), plus the disclosure rule;
• required: the specific AI task students do, how they evaluate and correct the output, and what they submit to show their judgement (prompts, outputs, critique).

1. Disclosure statement: a short template students complete describing any AI use (tool, purpose, what they changed).
2. Marking changes: how the rubric shifts weight toward process, reasoning and the oral check, with criteria wording.
3. Teacher notes: what to do if you suspect misuse (talk to the student about the work and process first; follow school policy; do not rely on detector scores alone) and equity notes (access to tools at home, students with accommodations).

• Never claim the design makes AI use impossible or detectable. Say how it makes learning visible instead.
• Do not recommend AI-detection software as evidence of misconduct.
• Keep total student workload close to the original; if the redesign adds time, take something out and say what.
• Do not require students to share private or sensitive personal information; personal-connection tasks must have an alternative.
• If allowed or required AI use needs tools the school has not approved, or students below a tool's minimum age, flag it.
• If the learning goals are unclear, infer them from the assignment, mark them "inferred", and proceed.

Diagnosis

Bullets: vulnerable parts → goals not evidenced.

Redesigned assignment

The new student-facing brief.

Process checkpoints

Table: Checkpoint | Due | Students submit | Feedback.

Oral check

Protocol, questions, what a secure answer sounds like.

AI-use policy for students

Student-facing, under about 200 words.

Disclosure statement

Template.

Marking changes

Criteria and weights.

Teacher notes

Bullets.