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Broadening conceptions of learning in medical education: the message from teamworking.

机译:扩大医学教育中的学习观念:团队合作的信息。

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Background There is a mismatch between the broad range of learning theories offered in the wider education literature and a relatively narrow range of theories privileged in the medical education literature. The latter are usually described under the heading of 'adult learning theory'. Methods This paper critically addresses the limitations of the current dominant learning theories informing medical education. An argument is made that such theories, which address how an individual learns, fail to explain how learning occurs in dynamic, complex and unstable systems such as fluid clinical teams. Results Models of learning that take into account distributed knowing, learning through time as well as space, and the complexity of a learning environment including relationships between persons and artefacts, are more powerful in explaining and predicting how learning occurs in clinical teams. Learning theories may be privileged for ideological reasons, such as medicine's concern with autonomy. Conclusions Where an increasing amount of medical education occurs in workplace contexts, sociocultural learning theories offer a best-fit exploration and explanation of such learning. We need to continue to develop testable models of learning that inform safe work practice. One type of learning theory will not inform all practice contexts and we need to think about a range of fit-for-purpose theories that are testable in practice. Exciting current developments include dynamicist models of learning drawing on complexity theory.
机译:背景技术在广泛的教育文献中提供的广泛学习理论与医学教育文献中相对较窄的理论特权之间存在不匹配。后者通常在“成人学习理论”的标题下进行描述。方法:本文主要探讨了当前主导医学教育理论的局限性。有人提出这样的理论,即针对个人学习方式的理论,无法解释在动态,复杂和不稳定的系统(如流动的临床团队)中学习是如何发生的。结果考虑到分布式知识,通过时间和空间进行学习以及学习环境的复杂性(包括人与人为因素之间的关系)的学习模型在解释和预测临床团队中学习的发生方式方面更为有效。学习理论可能由于意识形态方面的原因而受到特权,例如医学对自主性的关注。结论在工作场所中发生越来越多的医学教育的地方,社会文化学习理论为此类学习提供了最合适的探索和解释。我们需要继续开发可测试的学习模型,以指导安全的工作实践。一种学习理论并不能为所有实践环境提供信息,我们需要考虑一系列在实践中可检验的适合目的的理论。令人兴奋的当前发展包括基于复杂性理论的动态学习模型。

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