Abstract for: Feedback Narratives with Loops That Matter: Using AI to Strengthen Understanding

This workshop provides a practical introduction to using Loops That Matter (LTM) in Stella Architect, including the sd‑ai platform to strengthen model‑based storytelling. Participants will learn how to move beyond analyzing equations and simulation outputs to develop clear, compelling feedback narratives that explain why models behave the way they do. The session will begin with a concise overview of feedback loop dominance analysis and the principle that system structure drives behavior. Participants will then explore LTM, enabling them to identify key feedback loops, interpret loop score variables, and recognize shifts in loop dominance across time. Through live demonstration, they will learn how reinforcing and balancing processes interact, how to name and describe feedback loops, and how to link structural insights to observed dynamics. AI integration through the sd‑ai platform gives participants an opportunity to enhance their written explanations, generate concise loop descriptions, and explore narratives. In small groups, participants will conduct an LTM analysis of their own models, documenting loops, dominance shifts, and generating an overall feedback narrative. By the end of the workshop, attendees will be able to combine LTM analysis, and AI‑supported reasoning to construct rigorous and accessible feedback narratives that illuminate system behavior.