Identifying learners' behavior from videos affects teaching methods of lecturers in Universities
Automated learning behavior analysis of learners is becoming an essential topic in the field of education, where effective systems are needed to monitor learning progress and provide necessary feedback to instructor activities. teach. Recent advances in the application of computer vision allow automatic monitoring of behavior and attention status of learners at different levels, from elementary school students to college students.The goal of this study is to develop an automated system that allows schools to capture and summarize student behavior in the classroom as part of data collection for decision-making. . The system records the entire session and determines when students pay attention in the classroom, then reports it to the facility. Our experiments show that assessing the behavior of learners in the class from the video combined with a number of algorithms brings high accuracy. On that basis, adjust the content and teaching methods suitable for each learner. One of the ways to detect student attitudes is through students' gestures and postures in the classroom.