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The Replication Crisis in Empirical Science: Implications for Human Subject Research in Mixed Reality

机译:经验科学的复制危机:对混合现实中的人类主题研究的影响

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This tutorial will first discuss the replication crisis in empirical science. This term was coined to describe recent significant failures to replicate empirical findings in both medicine and psychology. In many cases, over 50% of previously reported results could not be replicated. This fact has shaken the foundations of both fields: Can empirical results really be believed? Should, for example, medical decisions really be based on empirical research? After describing the crisis, the tutorial will revisit enough of the basics of empirical science to explain the origins of the replication crisis. The key issue is that hypothesis testing, which in empirical science is used to establish truth, is the result of a probabilistic process. However, the human mind is wired to reason absolutely: Humans have a difficult time understanding probabilistic reasoning. The tutorial will discuss some of the ways that funding agencies, such as the US National Institutes of Health (NIH), have responded to the replication crisis, by, for example, funding replication studies, and requiring that grant recipients publically post anonymized data. Finally, the tutorial will consider how the Virtual Environments community might respond to the replication crisis. In particular, in our community the reviewing process often considers work that involves systems, architectures, or algorithms. In these cases, the reasoning behind the correctness of the results is usually absolute. Therefore, the standard for accepting papers is that the finding exhibits novelty - to some degree, the result should be surprising. However, this standard does not work for empirical studies (which, typically, involve human experimental subjects). Because empirical reasoning is probabilistic, important results need to be replicated, sometimes multiple times, and by different laboratories. As the replications mount, the field is justified in embracing increasing belief in the results. In other words, consider a field that, in order to accept a paper reporting empirical results, always requires surprise: This is a field that will not progress in empirical knowledge. The tutorial will end with a call for the community to be more accepting of replication studies. In addition, the tutorial will consider whether actions taken by other fields, in response to the replication crisis, might also be recommendable for the Virtual Environments community.
机译:本教程将首先讨论经验科学的复制危机。该术语被创造为描述近期重大故障,以复制医学和心理学中的实证发现。在许多情况下,无法复制50%以前报告的结果。这一事实摇动了这两个领域的基础:可以识别经验结果吗?例如,应该基于实证研究的医学决策?在描述危机后,教程将重新审视经验科学的基础知识来解释复制危机的起源。关键问题是,在经验科学中用于建立真理的假设检测是概率过程的结果。然而,人类的思想是绝对有线的:人类有很难了解概率推理。本教程将讨论资助机构,例如美国国立卫生院(NIH)等一些方式,并通过提供复制研究,并要求授予收件人公开发布匿名数据的复制危机。最后,教程将考虑虚拟环境社区如何响应复制危机。特别是,在我们的社区中,审查过程通常会考虑涉及系统,架构或算法的工作。在这些情况下,结果的正确性原因通常是绝对的。因此,接受论文的标准是,发现表现出新颖性 - 某种程度上,结果应该是令人惊讶的。然而,本标准对实证研究(通常,涉及人类实验受试者)不起作用。因为经验推理是概率的,所以需要复制重要结果,有时是多次,以及不同的实验室。作为复制山,该领域是合理的,在采用越来越多的效果方面是合理的。换句话说,考虑一个领域,为了接受纸张报告经验结果,总是需要惊喜:这是一个不会在经验知识中取得的领域。教程将结束,并呼吁社区更加接受复制研究。此外,本教程将考虑是否响应复制危机的其他字段采取的动作,也可以为虚拟环境社区推荐。

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