Effects of biased hypothesis generation on self-directed category learning.

Effects of biased hypothesis generation on self-directed category learning.
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有偏见的假设生成对自我导向类别学习的影响。

DOI:
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发表时间:
2019
期刊:
Journal of Experimental Psychology. Learning, Memory and Cognition
影响因子:
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通讯作者:
D. Markant
D. Markant
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文献类型:
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作者:
D. Markant

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长期以来,心理学家和教育家一直指出自主学习的无数好处。然而,其在现实世界领域的有效性的证据是混合的,它仍然不清楚它是如何受到基本的感知和认知过程的限制。以前的研究表明,自我导向学习尤其受到人们在学习时产生假设的方式的影响。本研究探讨了有偏见的假设生成如何影响分类规则的学习,概念学习的基本组成部分,通过自我导向的训练数据的选择。在知觉和抽象类别学习任务中,参与者关于未知分类边界的假设受到特征表示方式的影响。尽管他们有机会控制训练项目的选择,但这种偏见对他们学习潜在分类关系的能力有持续的影响。结果表明,自我导向控制可以是有益的知觉和抽象的类别学习,但发现规则的一种特定形式的能力取决于学习环境如何引导新的假设的产生。(PsycINFO数据库记录(c)2018阿帕,保留所有权利)。
Psychologists and educators have long pointed to myriad benefits of self-directed learning. Yet evidence of its efficacy in real-world domains is mixed and it remains unclear how it is constrained by basic perceptual and cognitive processes. Previous work suggests that, in particular, self-directed learning is affected by the way that people generate hypotheses as they learn. This study examines how biased hypothesis generation affects the learning of categorical rules, a basic building block of concept learning, through self-directed selection of training data. In both perceptual and abstract category learning tasks, participants' hypotheses regarding an unknown classification boundary were influenced by how features were represented. This bias had persistent effects on their ability to learn the underlying categorical relationship despite their opportunity to control the selection of training items. The results demonstrate that self-directed control can be beneficial for both perceptual and abstract category learning, but that the ability to discover rules of a particular form depends on how the learning environment guides the generation of new hypotheses. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
DOI: 10.1037/0278-7393.29.4.650
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