Proceedings of the 2023 3rd International Conference on Education, Information Management and Service Science (EIMSS 2023)

<Previous Article In Volume
Next Article In Volume>

A Model for Analyzing the Behavior of Classroom Teacher-Student Interaction Based on Deep Learning

Authors
Mingyue Zhou1, Wei Pan1, *, Zelin Zhang1
1Capital Normal University, Beijing, 100048, China
*Corresponding author. Email: 5263@cnu.edu.cn
Corresponding Author
Wei Pan
Available Online 28 September 2023.
DOI
10.2991/978-94-6463-264-4_27How to use a DOI?
Keywords
educational analytics; video analytics; deep learning; intelligent analytics
Abstract

In the context of combining education and artificial intelligence, it is important to identify and analyze interactive behaviors in intelligent classroom behaviors. The main contribution of the article is the design and implementation of an intelligent analysis model of classroom teacher-student interaction behavior based on deep learning. In this study, we provide a method for encoding common teacher-student interactional behaviors, and we employ the YOLOv8 deep learning network to recognize these behaviors and to perform temporal and statistical analyses of the data: classroom videos are classified and analyzed for teacher-individual interaction, teacher-group interaction, teacher-class interaction, cross interaction and student-student interactions. The experimental results show that the detection results of this model can basically cover the detection results of the manual observation method with an average difference rate of less than 5%, which is of practical value for classroom teaching evaluation and teacher-student interaction behavior assessment.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

<Previous Article In Volume
Next Article In Volume>
Volume Title
Proceedings of the 2023 3rd International Conference on Education, Information Management and Service Science (EIMSS 2023)
Series
Atlantis Highlights in Computer Sciences
Publication Date
28 September 2023
ISBN
978-94-6463-264-4
ISSN
2589-4900
DOI
10.2991/978-94-6463-264-4_27How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Mingyue Zhou
AU  - Wei Pan
AU  - Zelin Zhang
PY  - 2023
DA  - 2023/09/28
TI  - A Model for Analyzing the Behavior of Classroom Teacher-Student Interaction Based on Deep Learning
BT  - Proceedings of the 2023 3rd International Conference on Education, Information Management and Service Science (EIMSS 2023)
PB  - Atlantis Press
SP  - 240
EP  - 250
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-264-4_27
DO  - 10.2991/978-94-6463-264-4_27
ID  - Zhou2023
ER  -