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相关概念视频

Cognitive Learning01:21

Cognitive Learning

219
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...
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Steps in the Modeling Process01:14

Steps in the Modeling Process

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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...
174
Associative Learning01:27

Associative Learning

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Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
Classical conditioning, also known...
288
Introduction to Cognitive Psychology01:20

Introduction to Cognitive Psychology

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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...
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Cognitivism01:17

Cognitivism

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Cognitive psychology emerged as a significant field in the mid-20th century. It focused on understanding humans' internal mental processes. This approach emphasizes how people perceive, remember, think, and solve problems—elements critical to human cognition.
Previously dominated by behaviorism, which prioritized observable behaviors and largely ignored mental processes, psychology transformed in the 1950s. Cognitive psychologists argue that understanding how we think and process...
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Natural and Artificial Concepts01:24

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In psychology, concepts can be divided into two categories: natural and artificial. Natural concepts are formed through direct or indirect experiences. For example, consider the concept of snow. If you live in a place with regular snowfall, such as Essex Junction, Vermont, you know snow through direct experiences. You’ve seen it fall, touched it, shoveled it, and played in it. You recognize its texture, appearance, and even its smell. In contrast, if you live on an island like Saint...
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相关实验视频

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Project-Based Learning Guidelines for Health Sciences Students: An Analysis with Data Mining and Qualitative Techniques
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基于深度学习算法的体育教育教学概念理解和认知模式构建,基于深度学习算法.

Long Zhao1, Guoping Wu2, Weining Shao3

  • 1Faculty of Medicine and Health, Al-Farabi Kazakh National University, Al-Farabi Avenue 71, Almaty, 050040, Kazakhstan.

Scientific reports
|December 29, 2024
PubMed
概括

本研究介绍了一种深度学习方法,以提高体育教育 (PE) 教学概念的理解和分析学生的认知模式. 提出的模型显著提高了概念掌握,并为个性化学习支持提供了准确的认知状态预测.

关键词:
协会学习 协会学习认知模式 认知模式概念理解 概念上的理解.深度学习是一种深度学习.超图形卷积的超图形卷积体育教育是体育教育的一部分.

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科学领域:

  • 教育技术的教育技术
  • 教育中的人工智能
  • 认知科学 认知科学

背景情况:

  • 提高学生对体育教育 (PE) 概念的理解是至关重要的.
  • 教师需要工具来有效地分析学生的认知模式.
  • 深度学习为分析复杂的学习数据提供了潜力.

研究的目的:

  • 开发一种基于协会学习的方法来理解PE教学概念.
  • 构建一个神经认知诊断模型来识别学生的认知结果.
  • 通过认知模式分析增强教学指导和个性化学习.

主要方法:

  • 利用深度学习算法,特别是卷积神经网络 (CNN),用于提取与PE教学概念相关的图像特征.
  • 开发了一种神经认知诊断模型,使用超图卷积来分析长期学生学习序列.
  • 经过训练和验证的模型使用广泛的数据集来评估准确性和预测能力.

主要成果:

  • 协会图卷积神经网络在9万个训练样本中实现了0.84的最高精度.
  • 认知诊断模型在三个数据集中显示了0.76,0.77和0.75的准确性.
  • 用关联图卷积神经网络,学生对体育概念和知识的掌握率增加了29%.
  • 认知模式诊断模型显示平均预测准确度为0.81 (范围从0.6到1.0).

结论:

  • 提出的模型在预测认知模式方面表现出高准确性和稳定性.
  • 开发的方法有效地识别学生的认知状态,支持教学指导.
  • 这种方法为体育教育中的个性化学习体验提供了坚实的基础.