Sandars, J. and Murdoch-Eaton, D. orcid.org/0000-0002-2246-8785 (2017) Appreciative inquiry in medical education*. Medical Teacher, 39 (2). pp. 123-127. ISSN 0142-159X
Abstract
The practice of medicine, and also medical education, typically adopts a problem-solving approach to identify "what is going wrong" with a situation. However, an alternative is Appreciative Inquiry (AI), which adopts a positive and strengths-based approach to identify "what is going well" with a situation. The AI approach can be used for the development and enhancement of the potential of both individuals and organizations. An essential aspect of the AI approach is the generative process, in which a new situation is envisioned and both individual and collective strengths are mobilized to make changes to achieve the valued future situation. The AI approach has been widely used in the world of business and general education, but is has an exciting potential for medical education, including curriculum development, faculty development, supporting learners through academic advising and mentoring, but also for enhancing the teaching and learning of both individuals and groups. This AMEE Guide describes the core principles of AI and their practical application in medical education.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2016 Taylor & Francis. This is an author produced version of a paper subsequently published in Medical Teacher. Uploaded in accordance with the publisher's self-archiving policy. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > The Medical School (Sheffield) > Academic Unit of Medical Education (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 14 Dec 2016 14:05 |
Last Modified: | 17 Nov 2017 01:38 |
Published Version: | https://doi.org/10.1080/0142159X.2017.1245852 |
Status: | Published |
Publisher: | Taylor & Francis |
Refereed: | Yes |
Identification Number: | 10.1080/0142159X.2017.1245852 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:109397 |