How to Use AI to Prepare a Classroom Discussion or Debate

A discussion becomes a learning activity when participants work with reasons, listen to another position, and refine their own conclusion. AI helps suggest questions, alternative arguments, and original cases. However, it can easily create two caricatured sides or fill them with invented facts. Instructors need a subject that permits honest reasoning and rules that leave room for different voices. The loudness of a speech and number of remarks must not replace the quality of work with evidence.

This article's hypothetical case concerns dividing sixty minutes of a practical lesson between an instructor's demonstration and participants' independent work. The group must choose a plan within given constraints and identify its weakness. This is an original situation, not a study of method effectiveness or an actual institutional decision. We will use it to prepare positions, check arguments, plan individual work, moderate, and conclude. AI is neither a source of statistics nor the judge of a winner here.

State the Learning Outcome

For our lesson, the outcome is a reasoned recommendation with a condition for its application. Participants refer to case data, recognize a tradeoff, and answer one objection. The objective is not to convince everyone at any cost. A person may change their position or retain it while clarifying its boundary. Explain this before starting. Otherwise, the debate format may direct attention toward winning when you want to teach responsible reasoning.

The Eberly Center's material on discussions considers them opportunities to articulate positions, assess evidence, and engage with other perspectives. Cornell Center for Teaching Innovation also emphasizes dialogue's learning role. These sources provide general pedagogical context. The conditions, timing decisions, remarks, and criteria below are the author's design for a particular exercise, not a ready-made university script.

Keep the Case Self-Contained

The hypothetical group consists of twelve adults. They have already seen a short example of the action but have not yet performed it independently. During the new lesson, they must create a small output and explain one choice of their own. Total time is sixty minutes. Ten minutes are reserved for the final explanation. The remaining fifty must be divided between demonstration and practice. These are the exercise's starting facts, not a statistical description of typical learning.

Plan A allows twenty minutes for demonstration and thirty for practice. Plan B allows ten for demonstration and forty for practice. Both fit the time together with the conclusion. The case does not state each participant's working speed or the quality of the earlier example. Acknowledge these unknowns. Do not let AI fill them with 'everyone already understands well' or 'beginners always need a long explanation.' The boundary of the data is precisely what makes the choice meaningful.

Formulate a Question Without a Hidden Answer

A question could be: 'Which plan do you recommend for this group, what is your basis, and under what circumstance would you change your decision?' It allows different positions but requires working with the conditions. Do not ask, 'Why should we choose the obviously better Plan B?' That turns discussion into guessing the instructor's position. Likewise, 'Which is better: theory or practice?' is too broad and disconnects the conversation from the specified time and output.

You can ask AI to check whether the question leaves fair room for both plans. But do not accept its assessment without examples. Have the tool show a possible rationale for each position and its limitations. If one side contains only a weak argument, revise the conditions or wording. Discussion does not require artificial equality between all claims. It needs sufficient grounds for real analysis of the alternatives you deliberately included in the teaching case.

A Prompt for Preparing Positions

Example: 'Using the hypothetical case below, suggest two reasoned positions. For each, name a fact from the conditions, its connection to the recommendation, a weakness, and a question for the other side. Do not add studies, quotations, or numbers absent from the material. Do not caricature a position. Show separately which data remains unknown.' Insert the full conditions and learning outcome after the prompt.

The position supporting A may rely on participants not yet having performed the action independently. An additional example could help them see the steps. Its limitation is less time for their own attempt. The position supporting B may rely on the previous short example and the need to create an output. Its limitation is that this example may be insufficient for some of the group. These are the author's possible arguments, not established facts about either plan's effectiveness.

Check the Type of Grounds

During editing, separate case facts, assumptions, and value priorities. 'There is a previous example' is a fact of the case. 'It is enough for everyone' is an assumption. 'We prioritize more time for an attempt' is a priority requiring explanation. If AI mixes these types, an argument looks stronger than it really is. Instructors must restore the labels so students can honestly check the conclusion and identify its dependence on unknown data.

Do not add fake references to support the sides. If the learning task needs actual research, prepare verified primary sources and allocate separate reading time. Our self-contained case works without empirical generalizations. Participants analyze the given situation and the decision's limits. That is enough to practice argumentation. Statistics invented by AI to sound persuasive merely create the wrong habit of using an authoritative appearance instead of an available evidential basis.

Discussion and Debate Emphasize Different Things

In a discussion, participants may jointly build a third option after analyzing A and B. In a debate, temporary sides defend the assigned plans and respond to objections. In either format, the final individual explanation should reveal the student's own conclusion. Their team role need not match their personal opinion. Say this explicitly so participants do not feel obliged to remain supporters of a position after the exercise ends.

Do not switch formats unnoticed. If you first announce a joint search and then assess how persuasively a side is defended, the requirement has changed. For the first run, choose one main format and an understandable output. AI can suggest both script versions, but the instructor must approve one. Having many options is no advantage if the group does not understand its role or how to complete the work.

Individual Preparation Before Speaking

Before the exchange, allow time to write a personal recommendation, one reason, and one question. This creates material for people who find it difficult to enter a conversation quickly. Participants should not have to invent their whole position while speaking. They can then exchange explanations in pairs or small groups. Instructors get a chance to see the substance before the whole-group discussion instead of assessing only those who first raise their hands.

If assigning sides, do so after explaining the hypothetical role. Allow time to prepare an argument even if someone personally favors the other plan. However, do not use a learning role to justify forcing people to defend degrading or harmful claims. Our organizational case has no such need. Topic selection should match the learning objective and group circumstances, rather than a desire to make the conversation as confrontational as possible.

Roles Should Support Everyone's Contribution

In a small team, participants can divide the search for grounds, checking of limitations, and recording of the conclusion. Then rotate roles. One speaker must not do all the substantive work while others merely listen. Everyone needs their own notes for the final individual answer. If assessing a team output, state that separately. Do not attribute identical understanding to everyone simply because the group prepared a convincing presentation.

AI can help write short role instructions. Check that they do not create excessive mechanics. In a short lesson, a complicated system of judges, secretaries, and scorekeepers takes time away from reasoning. Our case needs only a few clear functions and one way to retain the conclusion. Roles support the learning action. They must not turn discussion into a game whose rules are harder than the subject being analyzed.

An Objection Tests the Connection

A useful objection does not attack the author. It questions the grounds or relationship: 'How do you know the previous example is enough?' or 'What will happen to the independent attempt if the explanation overruns?' Participants can answer with a condition of application rather than absolute certainty. The conversation then teaches them to refine an argument. 'Your plan is bad' identifies nothing to check and often merely increases tension without substantive benefit.

Prepare several objections of your own of different types: about unknown data, time allocation, and the final output. Do not present them as actual student questions. During class, use only what supports the actual conversation. If the group has already identified a weakness, do not mechanically repeat it according to the script. AI helps rehearsal, but live moderation should respond to what participants have actually contributed.

Rules and Human Moderation

For this case, agree on simple rules: critique the argument, show your grounds, do not attribute motives, leave room for others, and allow conclusions to change. State how personal remarks will be stopped. Instructors must intervene if discussion shifts from the plan to judging a person. Do not delegate decisions about who is behaving inappropriately to AI based on an incomplete text record. Context and group interaction require human observation.

If one side dominates, change the contribution format: a minute of written preparation, short explanations in pairs, or collecting questions. Do not demand identical numbers of public contributions as the only evidence of work. Participants can make important clarifications in writing. At the same time, an alternative channel must lead to the same substantive action. The objective is not comfort without analysis; it is an accessible opportunity to work with grounds and respond to objections.

Timing and a Change in Circumstances

A hypothetical forty-five-minute discussion can allocate five minutes to the conditions, seven to individual preparation, eight to teamwork, twelve to the exchange, six to a new circumstance, and seven to the final conclusion. This is the exercise's separate duration, not the sixty-minute lesson inside the case. Do not confuse these two levels of time. One describes organizing the learning discussion; the other is the subject of the decision students analyze.

A new circumstance could be this clarification: half the hypothetical group did not see the earlier example. Label it as the case's second version. Ask participants to reconsider their recommendation or add a condition. Do not declare the initial position 'wrong' if it matched the old data. The point is to see how a decision depends on information. This transfer teaches students to change an argument after clarification instead of sticking to a side merely to remain consistent in their presentation.

Checking Arguments Against the Case

Consider a hypothetical argument: 'Plan B is better because practice is always more effective.' It sounds persuasive but goes beyond the given data and contains an absolute generalization. Ask its author to return to the case: there has already been an example, and the final output needs an independent attempt. This is a possible basis for more practice time, but it depends on the example being sufficient. The revised argument must name that boundary. Students then learn to strengthen a position through a more precise connection between information, conditions, and a verifiable decision, rather than louder wording.

Another argument is: 'Plan A is needed because beginners know nothing.' This also changes the conditions. In the case, participants have seen an example, although they have not performed the action independently. It is more appropriate to say an additional demonstration may help reconstruct the steps before a first attempt. The limitation remains: less time for their own output. Ask AI to suggest such a clarification, but check that it does not add new characteristics to the group. An argument must not rely on a dismissive generalization about people merely to strengthen one side in a learning game.

A third argument proposes distributing part of the demonstration among groups, but does not explain who conducts it or how participants receive the example. This could be an idea for a third plan, but needs new resources. In discussion, it can be considered a conditional proposal; in a debate about A and B, it can wait until the conclusion. Do not call every creative alternative a ready-made solution. It too must pass checks on time, access, and the final output. AI readily adds a new format without considering exactly what constrains the original situation.

Two Levels of Questions About a Position

First check understanding of the data: how much time remains after the conclusion, what participants have already seen, and which output is needed. Then check the connection: why this information supports the chosen plan and what could change the conclusion. Do not ask every question simultaneously. Participants may answer the easiest and leave the main one untouched. A short sequence makes reasoning visible. At the same time, do not turn discussion into an interrogation where the instructor already knows the only solution and leads the group toward it through hidden hints in every remark.

For rehearsal, ask AI to write one answer at each level. Then check whether the second really explains the relationship instead of repeating a fact in different words. 'There is a previous example, therefore it exists' does not support a choice. You need to state how this might affect demonstration time and the quality of the first attempt. These original examples can be used for a brief teaching review before the debate. Label them hypothetical. Do not present a generated remark as an actual student answer or evidence that the whole group thinks that way.

What to Do with a New Fact During the Conversation

If participants bring an external claim about methods' effectiveness, ask for its source and an explanation of whether it fits the case. There is no need to accept it instantly as fact or reject it because it is inconvenient. For a self-contained exercise, agree that decisions rely only on the given conditions and external material is recorded for separate checking. This preserves fair shared grounds. Otherwise, one side might win through an unverified number others had no time to read, although the objective was to teach work with available data.

If the instructor adds a new circumstance, mark its status and allow time to revise the argument. Do not use clarification as a trap proving an earlier decision wrong. The initial recommendation may have been adequate under the old conditions. Now participants need to show the changed relationship. In our case, half the group not having seen the previous example may affect the choice or prompt a third plan. Participants must name exactly what changed. The conclusion then practices responsible updating rather than a contest over who can defend their first position longest despite new information.

An Individual Conclusion After Team Advocacy

After the presentations, give everyone a brief framework: 'My recommendation now is… The main grounds are… A limitation I acknowledge is… My answer to the objection is…' It does not name the correct plan, but helps retain all components. If participants keep their choice, ask what they have refined. If they change it, ask for the new grounds. A team role must not determine a personal conclusion. Students can say they defended A but, after analysis, recommend B under a certain condition. This change may be the most important learning outcome, invisible in a vote on the winning presentation.

To assess such a conclusion, check the data, connection, boundary, and answer to an objection. Do not add vocal confidence unless it is a separately announced objective. A well-formulated written argument may reveal more than an impressive presentation without grounds. If using AI to draft a comment, first reach a human judgment on the work. Machine text must not invent a motive for changing position. Participants may have revised a decision because of a specific circumstance, rather than insecurity or majority influence. Comments must stay within what is actually written and announced in the criteria.

A Fallback for Different Participation Speeds

If the whole-group exchange is fast and some people cannot keep up, introduce a short writing pause. Everyone records one question about an argument, then chooses whether to voice it. This reduces the demand to listen, formulate, and find an opening simultaneously. If conversation is slow, offer a specific pair of hypothetical explanations to compare. You do not need to answer for everyone immediately. The fallback changes how participants enter the activity while retaining analysis of grounds. Instructors must see whether participants lack time, subject-specific information, or a clear question, rather than explaining every case by one cause.

For an online version, check the available channel and prepare a private alternative for taking notes. Do not claim the platform automatically ensures equal participation. If you cannot collect every answer, use original examples and a final submission through an agreed method. Clearly state which evidence you will read. You cannot declare the whole group active or inactive based on one chat. A digital channel shows only part of behavior. A learning conclusion should rely on the necessary output and appropriate observations, not a convenient count of messages visible in the system during discussion.

Revising the Case for the Next Group

After running the activity, record which data was difficult to distinguish from assumptions and which question prompted substantive clarification. There is no need to collect a full record of every remark without need and permission. An anonymized note is often enough for the next revision: participants confused the exercise's duration with the lesson's duration inside the case. Then name the two levels of time more clearly. AI can help rephrase the conditions, but the author checks numbers and key relationships again. A change of form must not quietly make one plan obviously correct or remove fair room for another reasoned recommendation.

Keep the case, approved questions, rules, and conclusion framework as one package. Mark which data is hypothetical and what changes in the exercise's second version. For colleagues, it is useful to add why the topic was chosen: it allows practice in a bounded argument without unverified statistics. Do not pass on only a list of AI positions. It does not show how to run the lesson and finish with a learning output. An approved package helps preserve an honest dialogue where students can both defend an opinion and reconsider its basis after a new question or a change in available information.

A Conclusion Is More Than a Vote

At the end, everyone writes a recommendation, the main grounds, an acknowledged limitation, and an answer to one objection. Voting may show the distribution of choices but not the quality of explanations. Do not call the most popular plan proven. In our case, the result is a reasoned decision under the conditions. Retaining a position while stating its boundary more precisely is also a substantive change. The final work should reveal that development in reasoning.

The WeStudy LMS platform can be used for the conditions, rules, and final answer in your course. In WeStudy, keep the approved case version and separate initial data from later clarification, after checking the available format. AI helps prepare alternatives and rehearsal questions. Instructors are responsible for fair grounds, accessible participation, and a conclusion after which students can explain both their choice and the conditions under which it should be reconsidered.

Sources and Further Reading

• The Eberly Center's material on discussions

  
  

• Cornell Center for Teaching Innovation