Choosing the Right Chat Type for AI Case Simulations

You have a case study, a learning objective, and a decision you want students to wrestle with. The next question is how to present it: a sequence of messages and questions, a conversation with an AI character, or a case with multiple learner roles?

In LiveCase, those choices describe different aspects of the learning design. Chat types are the building blocks inside a case. You can combine multimedia, questions, and AI character conversations to create the experience your students need.

This guide explains how to choose those building blocks without confusing a teaching format with a separate product mode.

Structured Case Flows: Messages, Media, and Questions

A structured case flow lets you decide what students encounter and where they need to respond. LiveCase combines multimedia and question types within a case. Choose the format that best helps students examine evidence and explain a decision.

Use these building blocks when students need to examine evidence, make a choice, and explain their reasoning. A structured flow can follow a common sequence or use authored branching to show different content based on earlier answers.

When it works best: Guided case analysis, knowledge checks, and decisions that depend on a specific set of evidence.

Illustrative case design: A business student watches a CEO's briefing, examines a market chart, ranks three expansion options, and writes a justification for the chosen strategy. The instructor can use the submitted answers and rankings to prepare a debrief.

Choose a question format that matches the thinking you want to observe. Ask students to prioritize when trade-offs matter, select from defined options when you want a clear decision, or write an argument when their reasoning is the focus. A mix of these can reveal more than one final recommendation.

Avoid treating the resulting data as a direct measure of a student's internal thought process. An answer or response time can prompt a useful question in the debrief, but it does not by itself tell you why someone hesitated.

Related reading on AI case simulations: Beyond the Final Paper: Assess Decisions and Reasoning.

AI Character Conversations: Responsive Individual Practice

Use an AI character conversation when the learning objective requires a student to ask questions, respond to a stakeholder, or develop an argument through conversation.

When designing the activity, define the character's role, relevant knowledge, and the task the student needs to accomplish.

An individual AI character conversation gives each student an opportunity to practice questioning, listening, and responding.

When it works best: Negotiation, stakeholder interviews, difficult conversations, and practice explaining or defending a decision.

Illustrative case design: A student interviews a skeptical client before recommending a service. The character has information about the client's priorities and constraints. The student's questions determine which issues the conversation explores.

Responses can vary between conversations. That does not mean the platform guarantees a new personality or a different underlying scenario every time. If different conditions matter to the lesson, build and test those conditions deliberately.

AI grading and feedback can be configured for AI character conversations and written answers against author-defined criteria. Define what a strong response should demonstrate, then review the resulting feedback as part of your assessment process.

Present Competing Perspectives Before a Decision

An authored exchange between characters can give students several viewpoints to consider before they respond. As a teaching design, it is useful when the disagreement itself contains evidence students need to interpret.

When it works best: Introducing competing perspectives, presenting a disagreement, or preparing students to evaluate a trade-off.

Illustrative case design: Write a short exchange in which a finance director argues for conserving cash while an operations manager warns about capacity limits. Present those perspectives in the case content, then ask students which concern should take priority and why.

Keep the exchange focused on information students will use. This prepared content serves a different learning purpose from an open conversation with an AI character.

Multiple Learner Roles: Design the Case Around Different Perspectives

LiveCase cases can include multiple learner roles, and many existing cases do. Design each role around a clear responsibility and learning objective.

Start by deciding what each role is responsible for and what students should bring to the discussion. Then choose the content and interactions that support those responsibilities.

When it works best: Negotiation, cross-functional decision-making, and activities where students need to understand another stakeholder's constraints.

Illustrative teaching activity: Students take the perspectives of finance, marketing, and operations leaders considering a launch. Each role prepares a recommendation, and the class discusses the trade-offs between growth, cash, and delivery capacity.

For a specific case, check how roles are assigned, what each learner sees, and how participants coordinate. Multiple learner roles alone do not establish that AI automatically distributes different information, maintains a shared live outcome, or synchronizes every student's conversation.

Describe the actual case setup in your teaching instructions so students know which decisions happen in the platform and which happen through facilitated discussion.

Match the Building Block to the Learning Objective

You can combine these approaches inside a single case. For example, introduce the problem through multimedia, present competing viewpoints, invite students to question an AI character, and finish with a written recommendation.

FAQ

How do I choose the right interaction for my case?

Start with the learning objective. Use multimedia and questions to present evidence and capture decisions, AI character conversations to practice communication, and branching paths to explore different choices. Combine these within a case as needed.

Can a structured case branch?

Yes. Authors can design branching paths. A structured case does not have to give every learner identical content in an identical sequence.

When should I use prepared content instead of an AI conversation?

Use prepared content when students need a particular set of evidence before deciding. Use an AI character conversation when the learning objective depends on questioning, listening, and responding. You can combine both approaches.

Can a case include multiple learner roles?

Yes. Multiple learner roles are supported. The role instructions, information available to each learner, and coordination process depend on the case design.

Can I mix chat types within one case?

Yes. Combine messages, multimedia, questions, and AI conversations according to the learning objective. You do not need a separate simulation for every interaction format.

How should I start?

Choose one decision students need to make. Identify the evidence they need, select an interaction that exposes their reasoning, and plan the debrief. Then preview the case from the learner's perspective and check that the experience matches your intended lesson.