Presentation Schedule
AI-Assisted Debates: Prompt-Guided AI Use in Case-Based Teaching (107836)
Session Chair: Ling Yue
Saturday, 11 July 2026 13:30
Session: Session 3
Room: UCL Torrington, B08 (Basement Floor)
Presentation Type:Oral Presentation
Structured debate deepens case analysis by promoting evidence-based argumentation and engagement with opposing views (El Majidi et al., 2021). However, debate quality is often constrained by uneven student preparation: students may hold views on a case but struggle to develop structured arguments, anticipate counterarguments, and cite evidence under time pressure. This study evaluates a practical instructional response: instructor-engineered prompts that guide students’ use of generative AI for debate preparation, positioning AI as a scaffold for reasoning rather than an answer engine. The intervention was implemented in two undergraduate finance courses at a large Asian research university, where students completed two comparable case debates: under traditional preparation and AI-assisted preparation using a standardized, instructor-designed prompt. The prompt enforced step-by-step argument development, adversarial questioning, and evidence-based justification, while prohibiting direct solution generation; in both conditions, students participated in the same structured in-class debate format. Using a quasi-experimental, mixed-methods approach, the study draws on pre- and post-activity surveys, students’ preparation submissions, and audio recordings of in-class debates. Survey analysis indicates that guided AI preparation is associated with higher self-reported readiness, greater confidence in articulating and defending arguments, and improved perceived ability to engage with opposing viewpoints. Ongoing analysis examines whether these perceived gains correspond to observable differences in argument quality, evidence use, and responsiveness during debate. By shifting the focus from AI access to instructor-designed prompts, this study offers transferable principles for integrating AI into discussion-intensive teaching to strengthen students’ argumentation and engagement (Kasneci et al., 2023; Mollick & Mollick, 2023).
Authors:
Ling Yue, National University of Singapore, Singapore
Deserina Sulaeman, National University of Singapore, Singapore
About the Presenter(s)
Dr. YUE Ling is a Senior Lecturer of Finance at the National University of Singapore (NUS) Business School.
See this presentation on the full schedule – Saturday Schedule
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