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Learning with AI Language Models: Guidelines for the Development and Scoring of Medical Questions for Higher Education
Journal of Medical Systems ( IF 3.5 ) Pub Date : 2024-04-23 , DOI: 10.1007/s10916-024-02069-9
Thiago C Moulin 1, 2
Affiliation  

In medical and biomedical education, traditional teaching methods often struggle to engage students and promote critical thinking. The use of AI language models has the potential to transform teaching and learning practices by offering an innovative, active learning approach that promotes intellectual curiosity and deeper understanding. To effectively integrate AI language models into biomedical education, it is essential for educators to understand the benefits and limitations of these tools and how they can be employed to achieve high-level learning outcomes.

This article explores the use of AI language models in biomedical education, focusing on their application in both classroom teaching and learning assignments. Using the SOLO taxonomy as a framework, I discuss strategies for designing questions that challenge students to exercise critical thinking and problem-solving skills, even when assisted by AI models. Additionally, I propose a scoring rubric for evaluating student performance when collaborating with AI language models, ensuring a comprehensive assessment of their learning outcomes.

AI language models offer a promising opportunity for enhancing student engagement and promoting active learning in the biomedical field. Understanding the potential use of these technologies allows educators to create learning experiences that are fit for their students’ needs, encouraging intellectual curiosity and a deeper understanding of complex subjects. The application of these tools will be fundamental to provide more effective and engaging learning experiences for students in the future.



中文翻译:


使用人工智能语言模型学习:高等教育医学问题的开发和评分指南



在医学和生物医学教育中,传统的教学方法常常难以吸引学生并促进批判性思维。人工智能语言模型的使用有可能通过提供创新的、主动的学习方法来改变教学和学习实践,从而促进求知欲和更深入的理解。为了有效地将人工智能语言模型整合到生物医学教育中,教育工作者必须了解这些工具的优点和局限性以及如何利用它们来实现高水平的学习成果。


本文探讨了人工智能语言模型在生物医学教育中的应用,重点关注其在课堂教学和学习作业中的应用。使用 SOLO 分类法作为框架,我讨论了设计问题的策略,这些问题挑战学生锻炼批判性思维和解决问题的技能,即使在人工智能模型的辅助下也是如此。此外,我提出了一个评分标准,用于评估学生与人工智能语言模型合作时的表现,确保对他们的学习成果进行全面评估。


人工智能语言模型为提高学生参与度和促进生物医学领域的主动学习提供了一个有前途的机会。了解这些技术的潜在用途使教育工作者能够创造适合学生需求的学习体验,鼓励求知欲和对复杂学科的更深入理解。这些工具的应用对于未来为学生提供更有效、更有吸引力的学习体验至关重要。

更新日期:2024-04-23
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