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相关概念视频

Cognitive Learning01:21

Cognitive Learning

240
Cognitive learning is based on purposive behavior, incidental learning, and insight learning.
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
Tolman introduced the idea that behavior is influenced by...
240
Purposive Learning01:22

Purposive Learning

119
E. C. Tolman emphasized the purposiveness of behavior — the idea that much of our behavior is goal-directed. For instance, employees who aim for a promotion work diligently to meet their targets. Tolman argued that when classical conditioning and operant conditioning occur, the organism acquires certain expectations. In classical conditioning, a child might fear a dog because they expect it to bite. In operant conditioning, a person might consistently work overtime because they expect a...
119
Generalization, Discrimination, and Extinction01:24

Generalization, Discrimination, and Extinction

552
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...
552
Introduction to Learning01:18

Introduction to Learning

381
Learning is the process of acquiring knowledge or skills through practice or experience, leading to long-lasting behavioral changes. This acquisition occurs through interaction with the environment and requires practice or experience. For instance, mastering a skill such as surfing requires considerable practice and experience, highlighting the essential role of repeated interactions with the environment in learning.
In contrast to learned behaviors, unlearned behaviors such as crying, sexual...
381
Observational Learning01:12

Observational Learning

171
Albert Bandura's observational learning, also known as imitation or modeling, occurs when a person observes and imitates another's behavior. It is a quicker process than operant conditioning. A well-known example is the Bobo doll study, where children who saw an adult acting aggressively towards the doll were more likely to act aggressively when left alone, compared to those who observed a nonaggressive adult. Many psychologists view observational learning as a form of latent learning...
171
Steps in the Modeling Process01:14

Steps in the Modeling Process

205
Albert Bandura's theory of observational learning identifies four critical processes: attention, retention, motor reproduction, and reinforcement or motivation.
Attention is the first necessary component for observational learning. It involves focusing on what the model is doing and saying. For example, if you decide to take a drawing class to enhance your skills, you need to pay close attention to the instructor's words and hand movements. The characteristics of the model significantly...
205

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相关实验视频

Updated: Jul 1, 2025

Using a Split-belt Treadmill to Evaluate Generalization of Human Locomotor Adaptation
08:04

Using a Split-belt Treadmill to Evaluate Generalization of Human Locomotor Adaptation

Published on: August 23, 2017

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系统的人类学习和概括从一个简短的教程与解释性反.

Andrew J Nam1, James L McClelland1

  • 1Department of Psychology, Stanford University, Stanford, CA, USA.

Open mind : discoveries in cognitive science
|March 4, 2024
PubMed
概括
此摘要是机器生成的。

成年人很快就会学习抽象推理任务,并且在训练之外进行概括. 与数学教育相关的策略掌握,提高了对新问题的表现,突出了从教学中学习.

关键词:
抽象是抽象的,抽象是抽象的解释 解释 解释概括的概括是一般化的.系统性的系统性.

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科学领域:

  • 认知心理学 认知心理学
  • 神经科学是一个神经科学.
  • 人工智能的人工智能是人工智能.

背景情况:

  • 人类的抽象推理和概括是关键的认知功能.
  • 了解学习机制对于人类认知和人工智能发展至关重要.
  • 之前的研究已经探索了基于规则的学习,但从有限的例子中对快速概括的研究较少.

研究的目的:

  • 研究人类抽象推理的速度和程度.
  • 为了确定参与者是否可以将学习的策略推广到训练数据范围之外.
  • 探索战略描述清晰度,任务掌握和概括能力之间的关系.

主要方法:

  • 开发了一个基于苏多库的抽象推理任务.
  • 素朴的苏多库成年人接受了简短的指导和反,训练范围狭窄.
  • 在训练范围之外的实践试验和转移题上评估了表现.
  • 收集和分析了参与者的战略描述.

主要成果:

  • 大多数参与者在10次试验内掌握了任务,并很好地概括了.
  • 成功的战略收购与更好的转让绩效相关联.
  • 不到一半的人获得了有效的策略;这与先前的代数/几何知识有关.
  • 战略描述的质量有所不同,影响了转让业绩.

结论:

  • 人类可以快速学习抽象推理任务,并有效地概括.
  • 明确的策略学习和清晰的表达对于强大的推理转移至关重要.
  • 教育背景影响抽象策略的获取,对人工智能建模提出了挑战.
  • 指示和解释是快速学习和概括的强大工具.