Constructing knowledge: the role of AI in medical learning.

IF 4.7 2区 医学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS Journal of the American Medical Informatics Association Pub Date : 2024-08-01 DOI:10.1093/jamia/ocae124
Aaron Lawson McLean
{"title":"Constructing knowledge: the role of AI in medical learning.","authors":"Aaron Lawson McLean","doi":"10.1093/jamia/ocae124","DOIUrl":null,"url":null,"abstract":"<p><p>The integration of large language models (LLMs) like ChatGPT into medical education presents potential benefits and challenges. These technologies, aligned with constructivist learning theories, could potentially enhance critical thinking and problem-solving through inquiry-based learning environments. However, the actual impact on educational outcomes and the effectiveness of these tools in fostering learning require further empirical study. This technological shift necessitates a reevaluation of curriculum design and the development of new assessment methodologies to measure its effects accurately. Additionally, the use of LLMs introduces significant ethical concerns, particularly in addressing inherent AI biases to ensure equitable educational access. LLMs may also help reduce global disparities in medical education by providing broader access to contemporary medical knowledge and practices, though their deployment must be managed carefully to truly support the training of competent, ethical medical professionals.</p>","PeriodicalId":50016,"journal":{"name":"Journal of the American Medical Informatics Association","volume":" ","pages":"1797-1798"},"PeriodicalIF":4.7000,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11258398/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the American Medical Informatics Association","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1093/jamia/ocae124","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0

Abstract

The integration of large language models (LLMs) like ChatGPT into medical education presents potential benefits and challenges. These technologies, aligned with constructivist learning theories, could potentially enhance critical thinking and problem-solving through inquiry-based learning environments. However, the actual impact on educational outcomes and the effectiveness of these tools in fostering learning require further empirical study. This technological shift necessitates a reevaluation of curriculum design and the development of new assessment methodologies to measure its effects accurately. Additionally, the use of LLMs introduces significant ethical concerns, particularly in addressing inherent AI biases to ensure equitable educational access. LLMs may also help reduce global disparities in medical education by providing broader access to contemporary medical knowledge and practices, though their deployment must be managed carefully to truly support the training of competent, ethical medical professionals.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
构建知识:人工智能在医学学习中的作用。
将大型语言模型(LLM)(如 ChatGPT)整合到医学教育中,既能带来潜在的益处,也会带来挑战。这些技术与建构主义学习理论相一致,有可能通过探究式学习环境提高批判性思维和解决问题的能力。然而,这些工具对教育成果的实际影响以及促进学习的有效性还需要进一步的实证研究。这种技术转变需要对课程设计进行重新评估,并开发新的评估方法来准确衡量其效果。此外,使用 LLMs 会带来重大的伦理问题,特别是在解决固有的人工智能偏见以确保公平教育机会方面。LLMs 还可以通过提供更广泛的获取当代医学知识和实践的机会,帮助减少医学教育中的全球差异,但其部署必须谨慎管理,以真正支持培养有能力、有道德的医学专业人员。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Journal of the American Medical Informatics Association
Journal of the American Medical Informatics Association 医学-计算机:跨学科应用
CiteScore
14.50
自引率
7.80%
发文量
230
审稿时长
3-8 weeks
期刊介绍: JAMIA is AMIA''s premier peer-reviewed journal for biomedical and health informatics. Covering the full spectrum of activities in the field, JAMIA includes informatics articles in the areas of clinical care, clinical research, translational science, implementation science, imaging, education, consumer health, public health, and policy. JAMIA''s articles describe innovative informatics research and systems that help to advance biomedical science and to promote health. Case reports, perspectives and reviews also help readers stay connected with the most important informatics developments in implementation, policy and education.
期刊最新文献
Efficacy of the mLab App: a randomized clinical trial for increasing HIV testing uptake using mobile technology. Machine learning-based prediction models in medical decision-making in kidney disease: patient, caregiver, and clinician perspectives on trust and appropriate use. Research for all: building a diverse researcher community for the All of Us Research Program. Learning health system linchpins: information exchange and a common data model. Oncointerpreter.ai enables interactive, personalized summarization of cancer diagnostics data.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1