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基于人工智能的系统用于检测学生的注意力水平.

Luis Marquez-Carpintero1, Monica Pina-Navarro1, Sergio Suescun-Ferrandiz1

  • 1University Institute for Computer Research, University of Alicante.

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概括

人工智能 (AI) 可以通过分析面部情绪,目光,姿势和生物识别数据来识别学生的注意力. 这使教师能够优化学习过程,并有效地重新吸引学生.

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科学领域:

  • 教育技术的教育技术
  • 计算机科学 计算机科学
  • 人与计算机的交互

背景情况:

  • 学生的注意力对于有效的学习至关重要.
  • 监测注意力的传统方法往往是主观的,耗时的.
  • 开发自动化系统可以提供客观的实时反.

研究的目的:

  • 提出一种人工智能 (AI) 系统,用于在课堂上自动识别学生的注意力水平.
  • 探索多个数据源的集成,以改善注意力检测.
  • 促进教师及时干预,以提高学生的参与度.

主要方法:

  • 利用人工智能分析面部情绪 (例如,快乐,悲伤,愤怒).
  • 采用深度学习技术,通过摄像头评估身体姿势和凝视方向.
  • 整合智能手表中的生物识别数据 (心率,惯性测量).
  • 通过咨询专家输入和现有研究来创建标记的数据集,以准确地注释数据.

主要成果:

  • 证明了将各种数据流 (面部,姿势,生物识别) 结合起来用于注意力水平识别的可行性.
  • 提出了一个注意力分类器的框架,能够实时监控课堂.
  • 探索了向教育工作者提供及时反的方法.

结论:

  • 人工智能驱动的学生情绪,目光,姿势和生物识别的分析提供了一种有希望的方法,可以自动检测注意力水平.
  • 这项技术可以为教师提供可操作的见解,以调整他们的教学方法.
  • 这些数据源的整合有可能显著优化教学过程.