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相关概念视频

Cognitive Learning01:21

Cognitive Learning

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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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Classification of Systems-I01:26

Classification of Systems-I

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Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
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An integrated healthcare system (IHS) is a set of organizations that provides for or arranges to provide coordinated and continuous service to a defined population. The IHS takes responsibility for that particular population's health status and outcome, both clinically and fiscally. An integrated healthcare system is a well-organized, well-coordinated, and collaborative network. The integrated delivery system is a network that connects different healthcare providers to deliver organized,...
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Classification of Systems-II01:31

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Continuous-time systems have continuous input and output signals, with time measured continuously. These systems are generally defined by differential or algebraic equations. For instance, in an RC circuit, the relationship between input and output voltage is expressed through a differential equation derived from Ohm's law and the capacitor relation,
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Health Information Technology and Healthcare Information System01:30

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Health Information Technology (HIT)
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智能教育系统以使用物联网的CBR推系统改进学习系统,使用物联网的CBR推系统改进学习系统.

Veeramanickam M R M1,2, Manisha Sachin Dabade3, Sita Rama Murty P4

  • 1Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India.

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概括

这项研究增强了智能辅导系统 (STS),使用物联网和基于案例的推理 (CBR) 进行个性化的电子学习. 通过推定制的在线资源,CBR模型显著提高了学习者表现,特别是对于缓慢学习者.

关键词:
人工智能的人工智能是人工智能.物联网的物联网,就是物联网.推系统是推系统.智能学习技术是一种智能学习技术.

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科学领域:

  • 智能学习系统智能学习系统
  • 电子学习技术 电子学习技术
  • 教育数据挖掘教育数据挖掘

背景情况:

  • 智能辅导系统 (STS) 在电子学习中越来越多地用于改善学习过程.
  • 个性化学习模式至关重要,这是由学习者参与和特定要求驱动的.
  • 现有的系统需要优化,以满足各种学习者需求和参与度.

研究的目的:

  • 设计和评估基于物联网的个性化学习系统,使用基于案例的推理 (CBR).
  • 通过根据个人需求定制学习路径来提高学习者参与度和表现.
  • 专注于专门为缓慢学习者开发一个STS推模型.

主要方法:

  • 开发了一个基于物联网的个性化学习系统,包含学习者要求,搜索历史,经验和熟练程度.
  • 实施基于案例推理 (CBR) 基于分类器的搜索模型进行结果分析.
  • 在个性化学习干预之前和之后使用测试评估分析学习者的表现.
  • 通过使用不同组大小的根平均平方误差 (RMSE) 评估推模型的性能.

主要成果:

  • 在使用基于CBR的个性化学习模型后,学习者的表现显著提高,响应率从42.57%上升到74.82%.
  • 该CBR模型在推适合个人学习者需求的在线学习资源方面表现出有效性.
  • 推模型显示,在550名学生的小组大小中,RMSE (10-20%) 较低,与1600名学生 (24%RMSE) 的小组大小相比,表现更好.

结论:

  • 拟议的基于物联网的STS与CBR推模型有效地增强了个性化的电子学习体验.
  • 该系统在通过识别和推适当的在线学习资源来支持缓慢学习者方面特别有前途.
  • 进一步的研究可以为更大的学生群体优化推模型,以提高绩效的一致性.