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

Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

392
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence of...
392
Cognitive Learning01:21

Cognitive Learning

1.0K
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...
1.0K
Automatic Processing and Automatic Social Behavior01:28

Automatic Processing and Automatic Social Behavior

215
Automatic processing refers to the cognitive operations that occur without conscious intent or awareness, playing a fundamental role in shaping social cognition and behavior. These processes enable individuals to navigate complex social environments efficiently by relying on mental shortcuts and pre-existing knowledge structures known as schemas. One of the most influential mechanisms underlying automatic processing is priming, which subtly activates mental representations through exposure to...
215
Introduction to Learning01:18

Introduction to Learning

954
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...
954
Observational Learning01:12

Observational Learning

838
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...
838
Associative Learning01:27

Associative Learning

1.2K
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...
1.2K

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

High glucose-primed HUVEC-derived extracellular vesicles encapsulated in microgels boost diabetic ischaemic flap regeneration via HIF-1α/VEGF pathway.

Journal of nanobiotechnology·2026
Same author

Rapid prediction of vancomycin-resistant <i>Enterococcus faecium</i> using MALDI-TOF mass spectrometry and machine learning.

Frontiers in microbiology·2026
Same author

Compensatory characteristics and influencing factors of the sagittal curvature of the maxillary arch based on three-dimensional fusion imaging.

European journal of orthodontics·2026
Same author

Lobar-level radiomic clustering reveals background lung changes associated with lung cancer risk: a new perspective for early screening.

Insights into imaging·2026
Same author

Development of a predictive model for postoperative erectile function recovery in male patients with incomplete traumatic cervical spinal cord injury.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society·2026
Same author

Self-stabilizing zero-profile 3D-printed vertebral body versus traditional titanium mesh-cage with plate in anterior cervical corpectomy and fusion: an open-label randomized controlled trial on efficacy and complications for cervical spondylotic myelopathy.

Journal of orthopaedic surgery and research·2026
Same journal

DARUMA: a gateway to fast and easy prediction of intrinsically disordered regions.

PeerJ. Computer science·2026
Same journal

Alzheimer's disease detection using a quantum deep neural network with Haralick feature extraction and simulated annealing optimization.

PeerJ. Computer science·2026
Same journal

Network anomaly detection using Deep Autoencoder and parallel Artificial Bee Colony algorithm-trained neural network.

PeerJ. Computer science·2026
Same journal

An anomaly detection model for multivariate time series with anomaly perception.

PeerJ. Computer science·2026
Same journal

Retraction: A wormhole attack detection method for tactical wireless sensor networks.

PeerJ. Computer science·2026
Same journal

Evaluation of mental disorder with prioritization of its type by utilizing the bipolar complex fuzzy decision-making approach based on Schweizer-Sklar prioritized aggregation operators.

PeerJ. Computer science·2026
查看所有相关文章

相关实验视频

Updated: Jan 17, 2026

Multimodal Protocol for Assessing Metacognition and Self-Regulation in Adults with Learning Difficulties
12:55

Multimodal Protocol for Assessing Metacognition and Self-Regulation in Adults with Learning Difficulties

Published on: September 27, 2020

9.0K

基于自适应学习算法和多式模式行为建模的智能教育系统.

Yuwei Li1, Botao Lu2

  • 1College of Physical Education and Health, Hubei Business College, Wuhan, China.

PeerJ. Computer science
|September 24, 2025
PubMed
概括
此摘要是机器生成的。

这项研究引入了人工智能驱动的适应性学习架构,通过多式联络数据融合和智能资源推来增强个性化的教育. 该系统在预测学生表现和推学习材料方面取得了很高的准确性.

关键词:
适应性学习是一种适应性学习.智能教育是一种智能教育.多模式融合多模式融合

更多相关视频

Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes
10:43

Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes

Published on: June 10, 2021

5.8K
Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

5.3K

相关实验视频

Last Updated: Jan 17, 2026

Multimodal Protocol for Assessing Metacognition and Self-Regulation in Adults with Learning Difficulties
12:55

Multimodal Protocol for Assessing Metacognition and Self-Regulation in Adults with Learning Difficulties

Published on: September 27, 2020

9.0K
Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes
10:43

Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes

Published on: June 10, 2021

5.8K
Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

5.3K

科学领域:

  • 教育中的人工智能
  • 教育技术的教育技术
  • 机器学习 机器学习

背景情况:

  • 对个性化和适应性学习体验的需求日益增长.
  • 需要智能系统来满足学生的个人需求.
  • 动态环境中的传统教育方法的局限性.

研究的目的:

  • 提出一种新的自适应式学习驱动架构.
  • 整合多式联络行为建模以实现增强个性化.
  • 开发一个个性化的教育资源推系统.

主要方法:

  • 多式融合 (MMF) 算法使用堆叠的否定自动编码器和受限制的博尔茨曼机器.
  • 适应性学习 (AL) 模块与学生资源交互图表和图表增强的对比学习.
  • 基于双MLP的增强机制,用于动态材料推.

主要成果:

  • 预测错误的显著减少 (MAE = 0.01,MSE = 0.0053). 这是一个很好的结果.
  • 在资源推中,高精度 (95.3%) 和回忆 (96.7%).
  • 通过废除研究和基准比较来验证货币市场基金和AL的有效性.

结论:

  • 拟议的架构为下一代人工智能驱动的教育平台提供了坚实的技术基础.
  • 该系统表现出强大的可扩展性,实时响应能力和高用户满意度.
  • 多式联网数据和先进的机器学习技术的有效整合推动了个性化的学习成果.