Author(s)

Jinyu Liu ¹, Congkai Lin ¹, Jialun Chen ¹, Yinxiao Yan ¹

Affiliation(s)

¹ Taizhou Vocational & Technical College, Taizhou, Zhejiang, 318000, China

Corresponding Author

Jinyu Liu

ABSTRACT

Advances in artificial intelligence technology have provided new technical support for smart education. This study constructs a real-time classroom behaviour analysis and teaching intervention system based on object detection algorithms, achieving automatic recognition of classroom behaviour, state assessment, and generation of intervention recommendations. The system adopts a 'perception–analysis–decision -feedback' closed-loop architecture, integrating a behaviour recognition module based on an enhanced YOLOv5 algorithm, a real-time analysis module employing a sliding window mechanism, and a decision module utilising hierarchical intervention strategies. Experimental results demonstrate that the system effectively enhances classroom engagement, learning outcomes, and teaching quality. It provides teachers with precise instructional decision support, promotes the deep integration of educational technology and teaching practice, and achieves intelligent teaching intervention alongside personalised learning guidance.

KEYWORDS

Object Detection Algorithm; Classroom Behaviour Recognition; Real-Time Analysis; Teaching Intervention; Smart Education

CITE THIS PAPER

Jinyu Liu, Congkai Lin, Jialun Chen, Yinxiao Yan, Research on Real-Time Analysis and Intervention of Classroom Behaviour Based on Object Detection Algorithms. Advances in Vocational and Technical Education (2025) Vol. 7: 204-211. DOI: http://dx.doi.org/10.23977/avte.2025.070229.

REFERENCES

[1] Huang Y, Xue X, Chen H, et al. A method for classroom behavior state recognition and teaching quality monitoring[J]. International Journal of Intelligent Computing and Cybernetics, 2025, 18(2): 382-396.
[2] Yang Q. Identification and Intervention of Behavior Patterns Among College Students Based on Big Data Analysis[C]//The World Conference on Intelligent and 3D Technologies. Singapore: Springer Nature Singapore, 2024: 473-484.
[3] Zhang Y, Qu W, Zhong G, et al. Students' classroom behavior detection based on human-object interaction model[C]//2022 8th International Conference on Systems and Informatics (ICSAI). IEEE, 2022: 1-6.
[4] Kumar N S, SivaKrishna K, Vamsi V, et al. Real-Time Student Activity Detection and Incident Monitoring Using Artificial Intelligence[C]//2025 3rd International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT). IEEE, 2025: 1213-1224.
[5] Aly M. Revolutionizing online education: Advanced facial expression recognition for real-time student progress tracking via deep learning model[J]. Multimedia Tools and Applications, 2025, 84(13): 12575-12614.
[6] Nguyen P D, Le N T, Bui K H, et al. A method for continuous student activity recognition from classroom videos[J]. International Journal of Machine Learning and Cybernetics, 2025: 1-25.
[7] Akash S, Dinesh V, Muthamil Selvan S. Systematic Review on Real-Time Students Behavior Monitoring using Machine Learning[C]//2023 International Conference on Inventive Computation Technologies (ICICT). IEEE, 2023: 233-237.
[8] Alruwais N M, Zakariah M. Student recognition and activity monitoring in e-classes using deep learning in higher education[J]. IEEE access, 2024, 12: 66110-66128.
[9] Adhatrao A S, Patil M B, Sanmukh S G, et al. AI-based Surveillance for Exam Integrity: Real-Time Detection of Abnormal Student Behavior[C]//2025 4th International Conference on Sentiment Analysis and Deep Learning (ICSADL). IEEE, 2025: 1236-1241.
[10] Gopal J V, Kumar N S, Prasad K S, et al. Mindful Insights: Exploring an AI-Based Student Tracking System for In-Depth Analysis of Student behaviour[C]//2024 10th International Conference on Advanced Computing and Communication Systems (ICACCS). IEEE, 2024, 1: 1891-1897.

Sponsors, Associates, and Links

---

• Advances in Educational Technology and Psychology
  
  
• Curriculum and Teaching Methodology
  
  
• Transactions on Comparative Education
  
  
• Applied & Educational Psychology
  
  
• Adult and Higher Education