2.1 Conversations in Beta: An Interactive Workshop on AI‑Generated Simulations

Michael Cournoyea, PhD, Assistant Professor, Teaching Stream, Faculty of Kinesiology and Physical Education
Tolulola Taiwo-Hanna, MSW, RSW, PhD Candidate, Factor-Inwentash Faculty of Social Work
Joelleann Forbes, MSW, RSW, Sessional Instructor, Factor-Inwentash Faculty of Social Work

Filtering the Noise: Tools, Trends, and Tensions                    

Educators across disciplines are increasingly exploring how Large Language Models (LLMs) might support richer forms of experiential learning. One emerging use case is the development of interactive simulations—dynamic, responsive scenarios that allow students to practice discernment, apply concepts, and experiment with different approaches in a low‑stakes environment.

In this interactive Jam Session, we share insights from a classroom pilot in which Copilot generated a conversational mental health scenario for second-year Master of Social Work students. The simulation prompted learners to navigate uncertainty and make contextually sensitive decisions while receiving immediate, adaptive feedback. Participants will have an opportunity to engage directly with this classroom pilot, as well as an alternative Copilot-generated simulation, to experiment with its affordances and limitations.

These activities will be followed by a guided discussion on pedagogical design. Together, we will examine the “signal” and “noise” in LLM adoption: What kinds of learning do LLM-powered simulations genuinely support? How do they complement or complicate existing instructional strategies? Where do ethical concerns—including bias, emotional impact, and the transparency of LLM-generated personas—require deliberate safeguards? How do we design LLM-enhanced learning experiences that prioritize equity, critical thinking, and deep learning?

Participants will then collaboratively explore how LLM-powered simulations might be adapted within their own disciplines, from clinical cases to conflict resolution exercises. By experimenting, reflecting, and co-designing, attendees will leave with practical strategies and concrete examples for using LLMs to support meaningful, thoughtfully structured learning experiences that extend beyond novelty and toward deeper engagement.

Participants are encouraged to bring their laptop or connected devices to fully participate in the simulation.