Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Cognitive Learning01:21

Cognitive Learning

981
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...
981
Introduction to Cognitive Psychology01:20

Introduction to Cognitive Psychology

2.2K
Cognitive psychology is the field of psychology dedicated to examining how people think. It attempts to explain how and why we think the way we do by studying the interactions among human thinking, emotion, creativity, language, and problem-solving, as well as other cognitive processes. Cognitive psychology studies how information is processed and manipulated in remembering, thinking, and knowing.
This field emerged in the mid-20th century, following a period dominated by behaviorism, which...
2.2K
Observational Learning01:12

Observational Learning

802
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...
802
Decision Making: P-value Method01:09

Decision Making: P-value Method

6.8K
The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim  is also stated. These statements can act as null and alternative hypotheses:  a null hypothesis would be a neutral statement while the alternative hypothesis can...
6.8K
Machines: Problem Solving II01:30

Machines: Problem Solving II

628
Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. Consider a lifting tong carrying a 100 kg load. It comprises movable sections DAF and CBG linked together with member AB.
628
Machines: Problem Solving I01:22

Machines: Problem Solving I

667
A toggle clamp is a mechanical device commonly used for holding and clamping objects in various applications, such as woodworking, metalworking, and assembly operations. Consider a toggle clamp subjected to a force of 200 N at the handle. The vertical clamping force can be calculated, provided the dimensions of the toggle clamp are known.
The toggle clamp system is a machine structure consisting of movable, pin-connected multi-force members that form a stabilized system to transmit forces. The...
667

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Cas9/sgRNA-mediated genome editing of citrus via mature tissue transformation enables both high-efficacy genome editing and early flowering.

Frontiers in plant science·2026
Same author

The Applications and Prescriptions of Motion Style Acupuncture Treatment for Musculoskeletal Pain: A Scoping Review of Clinical Controlled Trials.

Journal of pain research·2025
Same author

Inspiratory muscle resistance combined with strength training: effects on aerobic capacity in artistic swimmers.

Frontiers in sports and active living·2024
Same journal

Exploring psychological tradeoffs: Developing and demonstrating an R Shiny app for Pareto optimization.

Behavior research methods·2026
Same journal

The performance of Bayesian fit measures in detecting misspecified multilevel structural equation modeling.

Behavior research methods·2026
Same journal

Psychometric functions from multiple responses : Dedicated to the memory of Colin L. Mallows.

Behavior research methods·2026
Same journal

Low-cost, open-source, full-stack software and Arduino-based hardware for control of commercially available animal behavior systems.

Behavior research methods·2026
Same journal

PyNeon: A Python package for the analysis of Neon multimodal mobile eye-tracking data.

Behavior research methods·2026
Same journal

Talking surveys: How photorealistic embodied conversational agents shape response quality, engagement, and satisfaction.

Behavior research methods·2026
查看所有相关文章

相关实验视频

Updated: Jan 10, 2026

Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

2.2K

超越性能:基于POMDP的机器学习框架,用于专家认知.

Hao He1, Yucheng Duan2,3

  • 1Department of Psychological and Cognitive Sciences, Tsinghua University, Beijing, 100084, China.

Behavior research methods
|November 25, 2025
PubMed
概括
此摘要是机器生成的。

体育方面的专业知识涉及到增强的感官精度 (SP) 和适应性先前信念 (pB) 校准,而不仅仅是技能. 这种认知重组使专家能够更好地预测不确定性下的行为.

关键词:
认知建模认知建模专业知识 专业知识 专业知识机器学习 机器学习之前的信念 之前的信念感觉精确度的感觉精确度是什么

更多相关视频

Decoding Natural Behavior from Neuroethological Embedding
08:00

Decoding Natural Behavior from Neuroethological Embedding

Published on: October 3, 2025

569
Online Repetitive Transcranial Magnetic Stimulation of Dorsomedial and Dorsolateral Prefrontal Cortex in Cognition Decision Making, and Cognitive Dissonance
13:20

Online Repetitive Transcranial Magnetic Stimulation of Dorsomedial and Dorsolateral Prefrontal Cortex in Cognition Decision Making, and Cognitive Dissonance

Published on: December 5, 2025

599

相关实验视频

Last Updated: Jan 10, 2026

Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

2.2K
Decoding Natural Behavior from Neuroethological Embedding
08:00

Decoding Natural Behavior from Neuroethological Embedding

Published on: October 3, 2025

569
Online Repetitive Transcranial Magnetic Stimulation of Dorsomedial and Dorsolateral Prefrontal Cortex in Cognition Decision Making, and Cognitive Dissonance
13:20

Online Repetitive Transcranial Magnetic Stimulation of Dorsomedial and Dorsolateral Prefrontal Cortex in Cognition Decision Making, and Cognitive Dissonance

Published on: December 5, 2025

599

科学领域:

  • 认知科学 认知科学
  • 运动科学 运动科学 运动科学
  • 机器学习 机器学习

背景情况:

  • 了解专家和新手之间的差异对于技能获取至关重要.
  • 在不确定性下预期是一个重要的认知挑战.

研究的目的:

  • 预先调查区分专家和新手的认知参数.
  • 应用部分可观测的马尔科夫决策过程 (POMDP) 建模和机器学习来进行这项调查.

主要方法:

  • 48名参与者 (24名专家,24名新手) 进行了篮球预测任务.
  • 通过POMDP建模,提取了感官精度 (SP) 和先前信念 (pB) 参数.
  • 机器学习分类器分析了专家和初学者参数配置文件的独特性.

主要成果:

  • 与新手相比,专家显示出更高的SP和更中性的pB.
  • 专家的认知参数与POMDP模型更加一致.
  • 机器学习实现了>90%的分类准确度,根据SP和pB区分专家和新手.

结论:

  • 专业知识包括增强的感知过 (SP) 和灵活的先前知识使用 (pB).
  • 认知重组,而不仅仅是技能增长,定义了专业知识.
  • 双参数方法提供了基于模型的专家认知的观点.