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Knowledge skills and beetles: respecting the privacy of private experiences in medical education

机译:知识技能和甲虫:尊重医学教育中私人经历的隐私

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摘要

In medical education, we assess knowledge, skills, and a third category usually called values or attitudes. While knowledge and skills can be assessed, this third category consists of ‘beetles’, after the philosopher Wittgenstein’s beetle-in-a-box analogy. The analogy demonstrates that private experiences such as pain and hunger are inaccessible to the public, and that we cannot know whether we all experience them in the same way. In this paper, we claim that unlike knowledge and skills, private experiences of medical learners cannot be objectively measured, assessed, or directly accessed in any way. If we try to do this anyway, we risk reducing them to knowledge and skills—thereby making curriculum design choices based on what can be measured rather than what is valuable education, and rewarding zombie-like student behaviour rather than authentic development. We conclude that we should no longer use the model of representation to assess attitudes, emotions, empathy, and other beetles. This amounts to, first of all, shutting the door on objective assessment and investing in professional subjective assessment. Second, changing the way we define ‘fuzzy concepts’ in medical education, and stimulating conversations about ambiguous terms. Third, we should reframe the way we think of competences and realize only part of professional development lies within our control. Most importantly, we should stop attempting to measure the unmeasurable, as it might have negative consequences.
机译:在医学教育中,我们评估知识,技能和通常称为价值观或态度的第三类。尽管可以评估知识和技能,但按照哲学家维特根斯坦(Wittgenstein)的“甲壳虫”类比,这第三类是“甲虫”。这个比喻表明,公众无法获得诸如痛苦和饥饿之类的私人经历,而且我们不知道我们是否都以相同的方式经历它们。在本文中,我们声称与知识和技能不同,医学学习者的私人经历不能以任何方式客观地衡量,评估或直接获得。如果我们仍然尝试这样做,则有可能将其减少到知识和技能上—从而根据可衡量的内容而不是有价值的教育做出课程设计选择,并奖励像僵尸一样的学生行为而不是真正的发展。我们得出的结论是,我们不再应该使用表征模型来评估态度,情绪,同情心和其他甲虫。首先,这等于关闭了客观评估并投资于专业的主观评估。其次,改变我们在医学教育中定义“模糊概念”的方式,并激发有关模棱两可术语的对话。第三,我们应该重新构造我们对能力的思考方式,并意识到只有一部分专业发展属于我们的控制范围。最重要的是,我们应该停止尝试测量无法衡量的内容,因为它可能会带来负面影响。

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