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首页> 外文期刊>Journal of Experimental Psychology. General >Interactivity Fosters Bayesian Reasoning Without Instruction
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Interactivity Fosters Bayesian Reasoning Without Instruction

机译：互动促进了贝叶斯推理而无需教学

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Successful statistical reasoning emerges from a dynamic system including: a cognitive agent, material artifacts with their actions possibilities, and the thoughts and actions that are realized while reasoning takes place. Five experiments provide evidence that enabling the physical manipulation of the problem information (through the use of playing cards) substantially improves statistical reasoning, without training or instruction, not only with natural frequency statements (Experiment 1) but also with single-event probability statements (Experiment 2). Improved statistical reasoning was not simply a matter of making all sets and subsets explicit in the pack of cards (Experiment 3), it was not merely due to the discrete and countable layout resulting from the cards manipulation, and it was not mediated by participants' level of engagement with the task (Experiment 5). The positive effect of an increased manipulability of the problem information on participants' reasoning performance was generalizable both over problems whose numeric properties did not map perfectly onto the cards and over different types of cards (Experiment 4). A systematic analysis of participants' behaviors revealed that manipulating cards improved performance when reasoners spent more time actively changing the presentation layout "in the world" as opposed to when they spent more time passively pointing at cards, seemingly attempting to solve the problem "in their head." Although they often go unnoticed, the action possibilities of the material artifacts available and the actions that are realized on those artifacts are constitutive of successful statistical reasoning, even in adults who have ostensibly reached cognitive maturity.
机译：成功的统计推理源于动态系统，包括：认知主体，具有可能的动作的物质，以及在进行推理时实现的思想和动作。五个实验提供的证据表明，不仅可以通过自然频率陈述（实验1）而且可以通过单事件概率陈述（实验1）对问题信息进行物理处理（通过使用纸牌），而无需进行培训或指导，就可以大大改善统计推理。实验2）。改进的统计推理不仅是将所有集合和子集明确显示在纸牌包中的问题（实验3），这不仅是由于纸牌操作所造成的离散且可数的布局，而且并非由参与者的干预参与任务的水平（实验5）。问题信息的可操作性对参与者的推理性能的积极影响在其数字属性不能完美地映射到卡片上的问题以及不同类型的卡片上都是普遍的（实验4）。对参与者行为的系统分析表明，当推理者花更多时间主动更改“世界”上的演示文稿布局时，而不是花更多时间被动地指向卡片，看似试图解决问题时，操纵卡片可以提高性能。头。”尽管它们经常被忽略，但即使在表面上已经达到认知成熟的成年人中，可用的实质人工产物的动作可能性以及在这些人工产物上实现的动作也构成了成功的统计推理的基础。

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