One of the major tasks in online education is to estimate the concentration levels of each student. Previous studies have a limitation of classifying the levels using discrete states only. The purpose of this paper is to estimate the subtle levels as specified states by using the minimum amount of body movement data. This is done by a framework composed of a Deep Neural Network and Kalman Filter. Using this framework, we successfully extracted the concentration levels, which can be used to aid lecturers and expand to other areas.
翻译:在线教育的主要任务之一是估算每个学生的集中程度。 先前的学习限制仅使用离散状态对水平进行分类。 本文的目的是通过使用身体运动数据的最低数量来估计指定水平的微妙程度。 这项工作由一个深神经网络和卡尔曼过滤器组成的框架来完成。 利用这个框架,我们成功地提取了集中程度, 可用于帮助讲师, 并扩大到其他地区 。