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Debate is a universally acknowledged competency for its vital role in fostering essential skills such as analytical reasoning, eloquent communication, and persuasive argument construction. This is relevant in both formal educational settings like classrooms and informal venues such as after-school clubs. Traditional debate training methods often face challenges in facilitating personalized learning, primarily due to the difficulty of securing a debate partner. However, the emerging field of generative AI offers a promising alternative. This study evaluates the effectiveness of DEBO, a debate education application that utilizes ChatGPT, an advanced language model by OpenAI. Focusing on university students actively involved in a debate club, six volunteers tested DEBO and participated in interviews to provide insights. The findings reveal that DEBO notably enhances divergent thinking and features a comprehensive analytics dashboard for in-depth performance analysis. However, there are few limitations including occasional shortcomings in debate quality, minor inaccuracies, and the need for faster response times. The study underscores the transformative potential of advanced language models like ChatGPT in reshaping debate education, while also identifying areas for further improvement. [ABSTRACT FROM AUTHOR]

To date, documentation of two doses of measles-containing vaccine (MCV) has been accepted as confirmation of measles immunity among healthcare workers (HCWs). However, we encountered measles in an HCW who had received two doses of MCV. A patient with measles was admitted to our hospital. Among 62 exposed HCWs, one nurse who had previously received two doses of MCV was shown to be negative for anti-measles immunoglobulin G (IgG), and was confirmed to have measles 14 days after exposure. Based on this experience, we suggest that all HCWs should be tested for anti-measles IgG to confirm their immunity to measles. [ABSTRACT FROM AUTHOR]