Prepare the role-play
Define the persona, set the instructions, and choose individual or group conversations.
Bring your next case into conversation.
Create an AI persona participants can interview, question, and challenge—individually or in small groups. Follow the conversations live, offer guidance, and bring findings into your debrief discussion.
Dialog Lab is being piloted in Fall 2026. We hope to welcome additional professors in Spring 2027 to try it with their courses and help shape its development.
Entrepreneurship · Evaluating a business idea
Illustrative lab exchange
Maya Torres AI persona
An entrepreneur preparing to open a neighborhood café
Student group
You’re expecting 100 customers a day. What did you use to estimate that demand?
Maya · AI persona
The café near my office always has a line, and friends say they’d visit mine. I haven’t counted foot traffic at the location yet. I assumed the neighborhood would be just as busy.
Instructor note
What would you need to know about this location before recommending that Maya sign a lease?
From your learning goals to the class discussion
One activity. Conversation for many questions.
Give students a situation to explore and a character to engage with. You shape the activity from preparation through debrief.
Facilitate the conversation
Students choose their questions and follow up on what they hear. Watch the conversations live, send a nudge, or pause for a teaching moment.
Debrief what emerged
Bring the conversations’ findings into discussion. Use transcripts to examine the questions students asked and the evidence behind their recommendations.
Built around the instructor’s role
Design it. Guide it. Discuss it.
Design a character around your learning goals
Define the scenario, background, key facts, and assumptions students should investigate. The AI-assisted Persona Builder provides an editable starting point for your review.
Your scenario. Your learning goals. An editable persona.
Let students investigate together—or individually
Small groups share one conversation with a persona and can build on one another’s questions. Individual conversations support solo practice with the same activity structure.
One shared conversation per group.
Stay involved as the activity unfolds
Follow conversations live from the instructor dashboard. Send guidance to a conversation or pause the session to bring everyone back together.
Live visibility and conversation for your teaching judgment.
Bring the conversation into the debrief
Students work through evidence and conclusions together. Review transcripts and export conversation and participation records for reflection or your own assessment.
Student work you can revisit after the activity.
Beyond "Prompt-and-Paste" AI
Why not just paste a prompt into ChatGPT?
Pasting instructions into general chatbots is an easy first experiment, but it quickly breaks down in an active lab seminar. When learning requires inquiry, raw prompts leak secrets, isolate participants, leave instructors blind, and produce erratic conversations. Here is how Dialog Lab solves the limits of the manual approach.
Genuine Discovery vs. Prompt Leakage
The "Prompt-and-Paste" Limit: Giving away the game
When students paste a prompt or use Custom GPTs, they can inspect the persona’s instructions, private constraints, walk-away thresholds, and rubrics before typing a word. The learning scenario is spoiled before inquiry even starts.
How Dialog Lab Solves It: True server-side confidentiality
Private facts, stakeholder motivations, and blind spots are securely composed on the server and never exposed to the browser. Students must uncover critical information through strategic questioning, active listening, and probing follow-ups.
Asymmetric information preserves the pedagogical purpose of the case.
Collaborative conversations vs. solitary chat
The "Prompt-and-Paste" Limit: Solitary homework in a silo
Standard consumer chatbots are strictly 1-on-1. Participants sit alone at their screens, missing out on the peer debate, challenge, and consensus-building that makes interactive lab role-play so memorable.
How Dialog Lab Solves It: Real-time team role-play
Students join a collaborative conversation where they share their exchange with the persona. Together, they build on each other's inquiries and synthesize evidence in real time.
Turns isolated AI interaction into social, high-retention team learning.
Live Orchestration vs. Instructor Blind Spots
The "Prompt-and-Paste" Limit: Flying blind during class
Instructors have zero live visibility into conversations across the class. If a student gets stuck, drifts off-topic, or encounters a wild hallucination, the instructor cannot intervene until reviewing post-hoc links or papers.
How Dialog Lab Solves It: The live instructor cockpit
A centralized dashboard mirrors every conversation in real time. Instructors spot automated moderation cues, send broadcast guidance, pause conversations for teachable moments, or "rewind and branch" a conversation.
Keeps the instructor in the loop as an active facilitator, not a bystander.
Governed Pedagogy vs. Model Drift
The "Prompt-and-Paste" Limit: Inconsistent models & sycophancy
Students use different accounts and free tiers with varying capabilities. Chatbots frequently cave to student demands prematurely, ask passive questions like "Does that make sense?", or lose track of lesson objectives after a few turns.
How Dialog Lab Solves It: Governed pedagogy & transcripts
Enforce consistent pedagogical structure through multi-persona casting. Standardized model routing ensures equitable challenge, and one-click session exports provide full transcripts and participation data for grading and debrief.
A repeatable, reliable learning experience across the entire lab series.
Designed for courses where inquiry, evidence, and debrief matter.
Transform AI from a solitary study aid into a rigorous, collaborative lab simulation.
Born in the seminar
It started with a business idea—and better questions to ask.
Dialog Lab began in a small-business and entrepreneurship course. Students acted as consultants, interviewing an entrepreneur about a new business idea before recommending whether to proceed, revise the plan, or pursue a different direction.
Spring 2027 beta · Applications Open
Help Shape Dialog Lab
We’re looking for professors interested in trying instructor-designed AI role-play and sharing practical feedback.