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Decide what the writing should demonstrate
UNESCO’s guidance frames generative AI in education around human agency and pedagogical suitability. Cornell’s assignment-design guidance begins with learning outcomes. Together, these give a practical starting point: define the intellectual operation you want students to practice before deciding whether generation belongs in the task.
For an introductory course, that operation might be constructing a supported paragraph independently. For an advanced seminar, it might be evaluating competing explanations. Those goals can justify different boundaries. A restriction on generation can be appropriate for one task while a critique of generated text can serve another; neither choice should remain implicit in the instructions.
A proposed assignment: compare an explanation with the evidence
Imagine a seminar about how cities adapt to heat. Give students two assigned studies and a short explanation prepared for critique. Ask them to identify three consequential claims, locate supporting or contradictory passages and write a revised argument. If the explanation is AI-generated, tell students that and establish the permitted tools in advance.
This hypothetical task makes evidence selection observable. A student must distinguish an intervention studied in one setting from a recommendation for a different community. The mark would depend on the quality of that reasoning and the revision, rather than on making the original explanation sound more polished. No learning gain from this proposed design is claimed here.
Request a small, meaningful process record
Ask for an initial position, a source-to-claim note and a short account of one substantive revision. Keep the record proportional to the learning goal. Cornell’s attribution guidance explains that a basic AI citation may need supplementary documentation depending on the assignment and its objectives. Specify what is needed rather than demanding every interaction by default.
For the heat-adaptation example, the useful record might explain why the student removed a claim about effectiveness after inspecting a study’s outcome measure. A long prompt transcript would not automatically demonstrate that understanding. Choose evidence that reveals a decision and lets the student explain it in their own terms.
Supporting reading: [3]
Define the tool boundary and provide a workable alternative
Write the permitted operations in the assignment itself. For example, students might use an approved tool to suggest counterarguments while completing the source analysis independently. Explain whether translation, grammar feedback and generated paragraphs fall within that permission. Cornell emphasizes communicating when and how AI use is permitted and considering accessibility.
Do not make a paid subscription an unspoken prerequisite. In this proposed design, an instructor could supply the same generated passage to everyone or offer an equivalent non-AI critique exercise. Check access, privacy and institutional approval before requiring personal accounts or uploads. A choice of tool should not obscure the academic task students are expected to perform.
Keep feedback connected to the learner’s next decision
An assistant can suggest that a paragraph lacks a counterargument, but the student still needs to decide whether that criticism is relevant. Ask for a response to feedback: what was accepted, what was rejected and what evidence informed the choice. This is a proposed way to keep the student responsible for the final argument.
Avoid treating agreement with an assistant as the expected answer. The learner may reasonably reject a fluent suggestion because it misstates a source or answers a different question. Make space for that explanation in the rubric. Human agency becomes concrete when students can question the tool rather than merely document that they used it.
Supporting reading: [1]
Evaluate the assignment before expanding it
Pilot the task with a manageable group or a low-stakes activity. Look at whether students can explain their source choices and transfer the reasoning to a fresh example without the assistant. Note where the instructions caused confusion, which process records were useful and how much feedback the task required. These are suggested evaluation questions, not a validated assessment instrument.
Future writing practice could develop in several directions, depending on educational goals, policy and access. A defensible design therefore needs revision as well. Keep the central question stable: what can the learner now understand, decide and justify? The availability of generated prose changes the environment in which that question is asked; it does not answer it.
Questions about this topic
Will AI make essay assignments obsolete?
That is not established here. Writing can assess reasoning, source interpretation and revision; the assignment needs to make those goals and tool permissions clear.
Should every assignment require an AI transcript?
No universal requirement follows from this guide. Request proportionate records that help assess the stated learning goal and explain exactly what students should submit.
Sources and editorial notes
The supporting reading below informs our editorial guidance. Exercises and scenarios illustrate a method; they do not report a completed product test or measured learning outcome. Read our editorial policy or send a correction with a supporting source to info@ai-essay.com.