--- title: 'Creating open answer questions' description: 'Ask students to write a response, then mark it against the success criteria and model answer you set.' canonical: 'https://www.gonurture.com/tutorials/signal/creating-sessions/creating-open-answer-questions' siteGuide: 'https://www.gonurture.com/llms.txt' --- ![Creating open answer questions](https://www.gonurture.com/og/tutorials/creating-open-answer-questions.png) Teacher Ask students to write a response, then mark it against the success criteria and model answer you set. Updated 26 August 2026 Open answer questions ask students to write, rather than pick from options. Instead of marking against a right answer, you set out what a good answer contains, and each response is marked against that. **When to use it:** When the thinking matters more than the conclusion — explaining a process, justifying a position, describing a method, or anything where a multiple choice option would give the answer away. **Where you can use them.** Live quizzes and assessment sessions. Not in Engage sessions. ## Adding an open answer question **1\. Choose New question, then choose Open answer.** **Open answer** sits in the list of question types down the left-hand side, alongside Quiz and Poll. **2\. Write your question.** The formatting toolbar is available here, including maths notation and bullet lists. If you are writing for maths or science, see [using LaTeX for maths and science notation](https://www.gonurture.com/tutorials/signal/creating-sessions/using-latex-for-maths-and-science-notation.md). **On Signal Premium, you can generate the question instead of writing it.** When you select Open answer, a **Generate with AI** field sits at the top of the editor, prompting you to _“Describe the open answer you want to create”_. Type what you want and Signal’s AI produces the question, the success criteria and the model answer together — steps 2, 4 and 5 below, in one go. Everything it produces is editable. Read the next three steps even if you generate, because they explain what the criteria and model answer are actually doing, and a generated set is a starting point rather than a finished question. The criteria in particular are worth checking: they are what every student’s answer will be marked against. **3\. Set how much you want students to write.** Under **Participant answer**, choose Short, Medium or Long, or set Custom for an exact minimum and maximum. The editor shows you what each option means as you pick it. The minimum is worth some thought. Set it too high and you push students into padding; set it at zero and you will get one-word answers. A minimum that reflects the shortest genuinely complete answer works best. **4\. Write your success criteria.** These are the things a good answer contains. They are what the answer is marked against, so write them as observable claims rather than vague qualities. “Names the two reactants” works. “Shows good understanding” does not. **Two or three focused criteria work best.** A short, specific list gives you marking you can act on. A long one spreads the assessment thin and makes it harder to see what a class actually missed. You can hide the criteria from students if you want to — see step 6. Hidden criteria still do their job: they are what each student’s AI feedback is generated against. Hiding them changes what students see while they write, not how their answer is assessed or what they get back. **5\. Write a model answer.** One example of a complete answer. This is what the marking and any feedback are grounded in, so it does more work than it looks like it does. It does not have to read like something you would hand out. You can write it as a marking note, terse and to the point, if that is more useful to you. **6\. Decide what students see.** Two separate switches: - **Success criteria** are shown by default. Students can see what they are being marked against as they write. Turning them off is a deliberate choice, useful if seeing the criteria would give too much away. - **Model answer** is hidden by default. Setting it to show means students see your example alongside their result. If you hide the model answer, it is genuinely hidden. It never reaches the student’s device and any AI feedback will neither quote it nor mention that it exists. It still shapes the marking, which is the point of being able to hide it. Both switches are available on every plan. ## What students see A text editor with a live character count, which will not let them submit until they have met your minimum. **In a live quiz,** you reveal the model answer and the marking when you are ready, in your own time. **In an assessment session,** they get their result when they finish, along with personalised feedback where you have it switched on. That feedback is AI generated, and it is written against what you set up in the question: their answer is assessed on your success criteria and your model answer, and the feedback speaks to that specific answer rather than offering something generic. This is the reason step 4 and step 5 are worth spending time on. Vague criteria produce vague feedback, because the criteria are what the feedback is reasoning against. Personalised written feedback is only available in assessment sessions. A live quiz never reaches the moment it would be written, so the option does not appear in the editor at all for live sessions. That is not a fault. ## Can I write the feedback myself? Not in Signal. The personalised feedback described above is AI generated, and there is currently no way to add your own written comment to an individual student’s answer in a Signal session. If you need to write feedback on student work yourself, that is done in Nurture Assessments rather than in Signal. ## What you see back Written answers appear in the response list, and there is a summary of the written answers on the question results panel. An open answer is never marked simply Correct or Incorrect, because nothing was picked. The criteria breakdown is the result. You can also see whether an answer was typed or pasted in. Two FAQs cover what Signal does with that: [why a correct guessed answer counts as half](https://www.gonurture.com/tutorials/signal/troubleshooting/why-does-a-correct-guessed-answer-count-as-half.md) and [why low-effort explanations are excluded from AI insights](https://www.gonurture.com/tutorials/signal/troubleshooting/why-are-low-effort-explanations-excluded-from-ai-insights.md). ## Tips - **Write the criteria before the model answer.** The criteria are what you are actually assessing. The model answer is one way of meeting them, not the target. - **One question, one thing.** An open answer covering three ideas produces marking that is hard to act on. Three criteria on one idea is more useful than one criterion on three. - **Read a few by hand anyway.** The marking tells you whether criteria were met. It does not tell you what surprised you about how a class was thinking, and that is usually the useful part. [Previous Write a question with AI from a prompt](https://www.gonurture.com/tutorials/signal/creating-sessions/write-a-question-with-ai.md) [Next Using LaTeX for maths and science notation](https://www.gonurture.com/tutorials/signal/creating-sessions/using-latex-for-maths-and-science-notation.md) Related articles - [Adding a student reflection in a session](https://www.gonurture.com/tutorials/signal/running-a-session/adding-a-student-reflection-in-a-session.md) - [Using LaTeX for maths and science notation](https://www.gonurture.com/tutorials/signal/creating-sessions/using-latex-for-maths-and-science-notation.md) - [Why does a correct guessed answer count as half?](https://www.gonurture.com/tutorials/signal/troubleshooting/why-does-a-correct-guessed-answer-count-as-half.md) - [Why are low-effort explanations excluded from AI insights?](https://www.gonurture.com/tutorials/signal/troubleshooting/why-are-low-effort-explanations-excluded-from-ai-insights.md) Still stuck? 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