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大开眼界:使用丰富图片探索复杂性。

Eye opener: exploring complexity using rich pictures.

作者信息

Cristancho Sayra

机构信息

Centre for Education Research & Innovation and Department of Surgery, Health Sciences Addition, Schulich School of Medicine and Dentistry, Western University, Room 110B, N6A 5C1, London, Ontario, Canada,

出版信息

Perspect Med Educ. 2015 Jun;4(3):138-41. doi: 10.1007/s40037-015-0187-7.

Abstract

Historically, approaches to exploring complexity have mainly focused on the notion that complex problems must be deconstructed into simpler parts if we are to make sense of them; this is the so-called reductionist approach. When dealing with the complexity of human experience, however, deconstructing the experience without diminishing it is a daunting, perhaps impossible task. Researchers wishing to make sense of complex experiences often begin by interviewing the individuals at the centre of those experiences. But interviews can be frustratingly limited. Visual methods, such as drawings, are beginning to show promise for designing research that taps into the complexity of professional practice. The promise of visual methods may relate to a key notion in complexity research: 'disruptions'. In this paper I introduce the notion of 'disruptions' as articulated by complexity approaches from 'systems engineering' and suggest 'rich pictures' as an effective visual method to describe and understand complex problems in medical education research.

摘要

从历史上看,探索复杂性的方法主要集中在这样一种观念上,即如果我们要理解复杂问题,就必须将其解构为更简单的部分;这就是所谓的还原论方法。然而,在处理人类体验的复杂性时,在不削弱体验的情况下对其进行解构是一项艰巨的、甚至可能是不可能完成的任务。希望理解复杂体验的研究人员通常首先会采访处于这些体验核心的个体。但访谈可能会受到令人沮丧的限制。诸如绘图等视觉方法,对于设计能够深入探究专业实践复杂性的研究开始展现出前景。视觉方法的前景可能与复杂性研究中的一个关键概念有关:“干扰”。在本文中,我引入了“系统工程”复杂性方法所阐述的“干扰”概念,并提出“丰富图片”作为一种有效的视觉方法,用于描述和理解医学教育研究中的复杂问题。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2bfd/4456463/11f66a3c3d76/40037_2015_187_Fig1_HTML.jpg

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