CaseMaster: Designing and Evaluating a Probe for Oral Case Presentation Training with LLM Assistance

要旨

Preparing an oral case presentation (OCP) is a crucial skill for medical students, requiring clear communication of patient information, clinical findings, and treatment plans. However, inconsistent student participation and limited guidance can make this task challenging. While Large Language Models (LLMs) can provide structured content to streamline the process, their role in facilitating skill development and supporting medical education integration remains underexplored. To address this, we conducted a formative study with six medical educators and developed CaseMaster, an interactive probe that leverages LLM-generated content tailored to medical education to help users enhance their OCP skills. The controlled study suggests CaseMaster has the potential to both improve presentation quality and reduce workload compared to traditional methods, an implication reinforced by expert feedback. We propose guidelines for educators to develop adaptive, user-centered training methods using LLMs, while considering the implications of integrating advanced technologies into medical education.

著者
Yang Ouyang
ShanghaiTech University, Shanghai, China
Yuansong Xu
ShanghaiTech University, Shanghai, China
Chang Jiang
Shanghai Clinical Research and Trial Center, Shanghai, China
Yifan Jin
ShanghaiTech University, Shanghai, Shanghai, China
Haoran Jiang
ShanghaiTech University, Shanghai, Shanghai, China
Quan Li
ShanghaiTech University, Shanghai, Shanghai, China

会議: CHI 2026

ACM CHI Conference on Human Factors in Computing Systems

セッション: People and Data

Area 1 + 2 + 3: theatre
7 件の発表
2026-04-17 18:00:00
2026-04-17 19:30:00