Writing Discussion Questions with AI

A discussion question is a teaching move, not merely a sentence with a question mark. Its value depends on what learners have read, the lesson purpose and what thinking they can reasonably do. A question that asks students to retrieve a stated fact may check orientation. A question about a decision, connection or evidence can open a deeper exchange. No single type is best for every moment. The Institute of Education Sciences’ materials for reading comprehension recommend focused, high-quality discussion of text meaning. They describe questions that prompt deeper thinking, follow-up questions that invite elaboration, and structured opportunities for students to lead small-group discussion. That guidance offers a practical test for AI-generated prompts: Does the question serve this text and instructional purpose, and can students support a response from the material? A generic prompt such as “What do you think?” may invite talk but leave the reasoning target unclear. An educator can give a model the exact passage, grade range, objective and limits, then request a small set of question types. For example, ask for one question about a character’s motive, one about how a detail changes an interpretation, and a follow-up that asks for evidence. Review every generated premise. Models sometimes invent plot details, assume a single interpretation, or write questions whose answers require knowledge the class has not studied. Questions also shape who can participate. Preview unfamiliar terms, allow thinking time, and offer more than one way to contribute. A student may speak, write, sketch a relationship, or discuss with a partner before sharing. Accessible wording does not require lowering the intellectual demand. It makes the task clearer while retaining the intended reasoning. Finally, use student responses as evidence: if the prompt produces only short guesses, adjust the scaffold or follow-up rather than concluding that learners have no ideas.