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相关概念视频

Generalization, Discrimination, and Extinction01:24

Generalization, Discrimination, and Extinction

563
Generalization, discrimination, and extinction are key concepts in operant conditioning that influence how behaviors are learned and maintained.
Generalization occurs when a behavior reinforced in one context is performed in similar situations. For instance, a student who studies diligently for calculus and receives excellent grades might apply the same study habits to psychology and history, expecting similar results. Generalization shows how learning in one setting can influence behavior in...
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Stereotype Threat and Self-fulfilling Prophecies02:09

Stereotype Threat and Self-fulfilling Prophecies

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When we hold a stereotype about a person, we have expectations that he or she will fulfill that stereotype. A self-fulfilling prophecy is an expectation held by a person that alters his or her behavior in a way that tends to make it true. When we hold stereotypes about a person, we tend to treat the person according to our expectations. This treatment can influence the person to act according to our stereotypic expectations, thus confirming our stereotypic beliefs. Research by Rosenthal and...
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相关实验视频

Updated: Jul 5, 2025

Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues
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Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues

Published on: June 3, 2013

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高可变性训练不会在原型-扭曲范式中增强概括性.

Mingjia Hu1, Robert M Nosofsky2

  • 1Psychological and Brain Sciences, Indiana University, 1101 E. Tenth Street, Bloomington, IN, 47405, USA.

Memory & cognition
|January 16, 2024
PubMed
概括

当训练试验被等同时,高可变性训练并没有改善点模式分类任务中的概括性. 这挑战了经典的发现,表明低变化培训可能对更简单的类别结构优越.

科学领域:

  • 认知心理学 认知心理学
  • 人类分类学习学习学习

背景情况:

  • 经典研究表明,高变量训练在原型扭曲范式中增强了概括性.
  • 最近的研究表明,当试验数量等同时,低变量训练优越.

研究的目的:

  • 通过使用经典的点模式刺激,重新评估训练可变性对概括的影响.
  • 调和关于培训变性和类别学习的相互矛盾的发现.

主要方法:

  • 采用原型扭曲范式与点模式刺激.
  • 在高可变性和低可变性条件中等同训练试验的数量.
  • 使用示例和原型模型进行数据分析.

主要成果:

  • 高变量训练并没有提高点模式任务的概括性,即使进行了广泛的训练.
  • 低变量的训练产生了类似或更好的概括性能.
  • 样本和原型模型有质地捕获了观察到的结果.

结论:

  • 高变量训练并不总是提高原型扭曲任务的概括性.
  • 培训变化的有效性可能取决于类别的复杂性.
  • 需要进一步的研究来探索在更复杂的类别结构中的培训效应.
关键词:
分类 分类 分类 分类 分类.计算建模计算建模一般化 一般化 一般化培训实例变化率的变化

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