One of the key limitations of the TBL 4S method is the “Specific Choice” component, which constrains responses to predefined options. Despite this feature being explicitly introduced in various Creative Application Exercise (AE) workshops at past TBLC conferences, not a single participant has opted to use it. Instead, facilitators and learners alike tend to favour open-ended responses, which encourage richer, more dynamic discussions.

With advancements in technology, we are now able to leverage Generative AI to automatically summarise vast amounts of team outputs from AEs, enhancing discussion quality and engagement. Even in large-scale TBL settings with 400+ concurrent users, AI-driven summarisation and pattern recognition enable facilitators to efficiently extract key arguments and themes, ensuring that discussions remain meaningful and aligned with learning objectives.

In this presentation, we will demonstrate how Generative AI can assist facilitators in guiding discussions, optimising learner engagement, and maintaining the pedagogical integrity of TBL sessions. Through this approach, we aim to bridge the gap between structured choice and open-ended discussions, ultimately enhancing the overall effectiveness of TBL.