Author(s)

Hongji Xu, Yonghui Yu, Renzhuo Wang, Xinya Li

Corresponding Author

Hongji Xu

Abstract

The learning status of students in the classroom is a crucial basis for evaluating the quality of teaching and learning. Therefore, conducting real-time analyses of students' classroom statuses and providing timely reminders for those in negative states can significantly improve the instruction. This paper proposes a real-time student status analysis system in the classroom that utilizes intelligent behavior and speech recognition techniques based on the multimodal data analysis. This scheme offers a solution to the issue of students' lack of attention and low learning outcomes in certain classroom. It can also generate a status report of the classroom which is very valuable for educators seeking to improve the quality of instruction and modify students' learning outcomes.

Keywords

Human Activity Recognition, Speech Recognition, Face Recognition, Classroom Evaluation