JOURNAL ARTICLE
Spatial Relevance: Teaching History to Medical Students at a Medical Museum in Hong Kong.
Published In: Journal of the History of Medicine & Allied Sciences, 2023, v. 78, n. 1. P. 71 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Wu, Harry Yi-Jui; Wong, Samson Ki Sum 3 of 3
Abstract
This article analyzes the pedagogical role and challenges of a mandatory history of medicine workshop for first-year medical students at the University of Hong Kong (HKU), conducted at the Hong Kong Museum of Medical Sciences (HKMMS). The workshop uses experiential learning through museum exhibits and a heritage trail to engage students with Hong Kong's medical history, focusing on the 1894 bubonic plague and the 2003 SARS epidemic, aiming to develop analytical skills related to historical contingency, disease causality, and multiple perspectives. While students generally find the spatial and narrative approach stimulating and relevant to their professional development, limitations include time constraints, a predominantly linear and clinician-led historiography, and difficulties in fostering deeper critical reflection due to curricular and cultural factors in East Asian medical education. The article highlights the need for ongoing curriculum adjustments, cross-disciplinary collaboration, and enhanced teaching infrastructure to better integrate medical humanities and historiographical thinking into medical training.
Additional Information
- Source:Journal of the History of Medicine & Allied Sciences. 2023/01, Vol. 78, Issue 1, p71
- Document Type:Article
- Subject Area:Politics and Government
- Publication Date:2023
- ISSN:0022-5045
- DOI:10.1093/jhmas/jrac043
- Accession Number:162697223
- Copyright Statement:Copyright of Journal of the History of Medicine & Allied Sciences is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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