Research on the Data Analysis of College Classroom Teaching Behavior by Using Deep Learning
- 10.2991/assehr.k.200401.014How to use a DOI?
- classroom behavior, pattern recognition, deep learning, correction matrix
With education stepping into the era of intelligence, intelligent classroom behavior recognition of students is becoming more and more important. However, due to the complexity and variety of students’ classroom behavior, it is difficult to recognize intelligent students’ classroom behavior. In order to improve the intensive reading of intelligent student behavior recognition, this paper uses a variety of data sources for cross comparison, and uses the mature random forest algorithm and correction matrix in the data analysis of classroom teaching behavior in Colleges and universities. Through the analysis, it shows that deep learning can timely and accurately feedback the classroom teaching phenomenon and the data and intelligence of teaching activities, which is conducive to the improvement of teaching methods, the optimization of classroom teaching and management, to improve the efficiency of teaching and learning and help the teaching reform.
- © 2020, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Bing Gong AU - Fan Jing PY - 2020 DA - 2020/04/06 TI - Research on the Data Analysis of College Classroom Teaching Behavior by Using Deep Learning BT - Proceedings of the International Conference on Education, Economics and Information Management (ICEEIM 2019) PB - Atlantis Press SP - 48 EP - 50 SN - 2352-5398 UR - https://doi.org/10.2991/assehr.k.200401.014 DO - 10.2991/assehr.k.200401.014 ID - Gong2020 ER -