Individualized Detection for Distant Learning Behaviors

• Main Authors: Hsu-Liang Tseng, 曾旭良
• Other Authors: Kuo-An Hwang
• Format: Others
• Language: zh-TW
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/70341946295464094332

碩士 === 朝陽科技大學 === 資訊工程系碩士班 === 99 === Distant learning has been extensively studied in the recent years. It is not only an educational approach that can be employed in remote areas, but also can serve as a supplementary tool when students and teachers are distantly located and unable to carry out face to face learning. However, due to insufficient self-control, students, when learning at home, are likely to be influenced by external objects, and thus, are not concentrated on learning. This study utilized the detection algorithm of image and computer. We installed a webcam on the desk of a student for facial detection. At first, a personal face department sample was setup. Then when the student studies at home, the facial features of the student are captured by the principle component analysis (PCA), and through in advance train of the image analyze. The learning status of the student is then determined based on the real-time facial features. Teachers and parents can guide learning behavior of the student, according to the students’ learning status, to overcome the distraction, and meet the goal of individualized learning.