Making assignments AI-robust

“Summarise the text and answer the questions.” An AI solves this homework in a few seconds.

The first reflex is a ban. That’s understandable. But what happens at home can hardly be controlled. Banning achieves little. Redesigning does.

The problem is the assignment, not the tool

An assignment that only asks for a finished product ends up mostly checking whether a text was handed in. You can’t tell from the text who wrote it.

So AI-robust doesn’t mean locking AI out. It means designing assignments in a way that makes real understanding visible.

Four building blocks

1. Process over product. Drafts, interim versions and notes are assessed too, not just the result. The ZHAW (Zurich University of Applied Sciences) explicitly provides for this in its guideline on AI in assessments: besides the end product, the working phase can be graded too, in other words a process assessment.

2. Local context. Connect the task to your class, your town or an experience from the lesson. What your class discussed last week is something no AI knows. It isn’t watertight: anyone who feeds the AI the context will still get an answer. But to do that, learners have to engage with what they experienced.

3. Oral defence. A short conversation quickly shows whether someone understands their own text. The ZHAW guideline mentions graded oral check-ins and defences. According to Swiss broadcaster SRF, oral formats are gaining weight at Swiss universities.

4. Let learners critique AI output. Learners check an AI answer, find mistakes and improve it. That turns AI from a shortcut into something to learn from.

Building blocks 1 and 3 are directly backed by the ZHAW guideline. Building blocks 2 and 4 are my own recommendations from teaching practice.

The examples come from school. In continuing education courses, the building blocks work the same way: the class becomes the course group, and the classroom becomes the training room or the participants’ own workplace.

The homework from the opening, redesigned

1. Instead of a summary, have an AI write one and give it to your learners with the task: mark what’s missing, what’s wrong and what you would weight differently.
2. Instead of generic questions, ask for a link to your lessons: where does the text contradict what you discussed in the last lesson?
3. Instead of just handing it in, have a conversation of a few minutes with some of the learners about their corrections. The notes from steps 1 and 2 count towards the grade.

That puts all four building blocks into one assignment. You control the effort yourself: you decide how many learners you talk to.

AI-robust doesn’t mean AI-free

None of these building blocks bans AI. It may help with research and wording, and it may even be the subject of the assignment. What has to stay visible is that the thinking is done by the learners.