Serviceeinschränkungen vom 12.-22.02.2026 - weitere Infos auf der UB-Homepage

Treffer: Addressing the needs and priorities of medical teachers through a collaborative intensive faculty development programme*.

Title:
Addressing the needs and priorities of medical teachers through a collaborative intensive faculty development programme*.
Authors:
Amin, Zubair1 (AUTHOR) paeza@nus.edu.sg, Hoon Eng, Khoo1 (AUTHOR), Gwee, Matthew1 (AUTHOR), Chay Hoon, Tan1 (AUTHOR), Dow Rhoon, Koh1 (AUTHOR)
Source:
Medical Teacher. Feb2006, Vol. 28 Issue 1, p85-88. 4p. 1 Chart.
Geographic Terms:
Database:
Education Research Complete

Weitere Informationen

Faculty development in medical education is crucial for developing and sustaining quality education in medical schools. However, examples of successful intensive programmes based on experiential and collaborative learning are generally lacking in the literature. The Medical Education Unit of National University of Singapore conducted a three-day intensive programme on core competences in medical education. This paper highlights the process of programme development, programme structure, challenges faced and strategies adopted. It also describes the approach taken to educational programme evaluation along with the results. The programme structure was based on experiential and collaborative learning models. Participants contributed to all activities and emerged as facilitators and learners to gain first-hand experience of the complex educational processes. Each individual session was sequential with a brief plenary, demonstration, practicum and reflection. Pre-programme needs assessment showed that even the experienced teachers perceived a need to further improve their educational competencies. [ABSTRACT FROM AUTHOR]

Copyright of Medical Teacher is the property of Taylor & Francis Ltd 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.)

Volltext ist im Gastzugang nicht verfügbar.