Video-based Student Classroom Classroom Behavior State Analysis

Authors

  • Yinggan Cheng

DOI:

https://doi.org/10.54097/ijeh.v5i2.2146

Keywords:

Education, Classroom behavioral states, Video images, Computer vision technology, Instructional feedback.

Abstract

Looking back on the development of education, education has evolved along with the development of human society, and the development of science and technology has been the fundamental force driving the change of education. And with the increasing demand for personalized education for students, the focus of education and teaching has gradually shifted to the direction of personalization and specialization of students. In the teaching process, students' classroom behavior is an important reference indicator for evaluating students' classroom learning, but teachers cannot pay attention to each student's classroom behavior in time, and can only derive students' classroom learning status from their homework or exams. Many subjective factors can easily affect teachers' judgment of students' learning status, and the evaluation obtained is not always comprehensive and objective enough. In traditional teaching activities, teachers mainly identify and control students' classroom videos manually, but this method is not only time-consuming and labor-intensive, but also affects teachers' classroom quality. Therefore, it is urgent to study an intelligent and effective system for analyzing students' classroom behavior status. It is of great significance to improve the quality of students' classroom learning and to assist teachers in obtaining teaching feedback information. At present, the rapid development of artificial intelligence is reshaping the world's industrial ecology and pushing human society into the era of intelligence. Artificial intelligence is deeply integrating with education and promoting innovation in educational philosophy, teaching methods and management modes, and is expected to lead systematic changes in education. In fact, the development of artificial intelligence technology cannot be separated from the continuous research of computer vision technology. How to make the computer obtain external information through video acquisition device to simulate human for analysis and recognition is the main research content of computer vision technology, and its research direction includes target tracking, object recognition, human behavior recognition, etc. In this paper, through the combination of artificial intelligence technology and computer vision technology, we analyze the video images of students' classes in classroom scenes, identify students' classroom behavior status, build a judgment system on students' classroom learning status, and assist teachers to obtain teaching feedback information.

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Published

27 October 2022

Issue

Section

Articles

How to Cite

Cheng, Y. (2022). Video-based Student Classroom Classroom Behavior State Analysis. International Journal of Education and Humanities, 5(2), 229-233. https://doi.org/10.54097/ijeh.v5i2.2146

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