<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The arrival of the big data era, which has been widely used in various industries. In today’s education management mode, in order to improve education development, it is necessary to keep up with the times and reform the education management mode. For this reason, this paper designs an education management model based on the classroom behavior recognition model, which manages students in real time by detecting their classroom behavior status. The classroom behavior recognition model is improved based on the deep learning target detection SSD algorithm. A lightweight model for detecting the behavior of SSD-M3-SFP networks has been designed by replacing the SSD backbone network, VGG, with a MobileNetV3 network after pruning SFPs. Both the speed and accuracy of student behavior recognition can be ensured by the model. Through practical analysis, in the before-and-after analysis of SSD-M3-SFP-based education management model and general education management model, the p-values are 0.001, 0.003, 0.000 on the indicators of the three aspects of education management services, all of which are lower than 0.05, and the difference is significant, and the management effect of SSD-M3-SFP-based education management model is higher than that of general education management model.</p>
</abstract>

The arrival of the big data era, which has been widely used in various industries. In today’s education management mode, in order to improve education development, it is necessary to keep up with the times and reform the education management mode. For this reason, this paper designs an education management model based on the classroom behavior recognition model, which manages students in real time by detecting their classroom behavior status. The classroom behavior recognition model is improved based on the deep learning target detection SSD algorithm. A lightweight model for detecting the behavior of SSD-M3-SFP networks has been designed by replacing the SSD backbone network, VGG, with a MobileNetV3 network after pruning SFPs. Both the speed and accuracy of student behavior recognition can be ensured by the model. Through practical analysis, in the before-and-after analysis of SSD-M3-SFP-based education management model and general education management model, the p-values are 0.001, 0.003, 0.000 on the indicators of the three aspects of education management services, all of which are lower than 0.05, and the difference is significant, and the management effect of SSD-M3-SFP-based education management model is higher than that of general education management model.

Research on the Reform of Educational Management Mode in Big Data Environment

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

{"article-title":"Research on the Reform of Educational Management Mode in Big Data Environment"}

The arrival of the big data era, which has been widely used in various industries. In today’s education management mode, in order to improve education...

Research on the Reform of Educational Management Mode in Big Data Environment

Publié en ligne: 05 août 2024

Pages: -

Reçu: 06 avr. 2024

Accepté: 03 juil. 2024

DOI: https://doi.org/10.2478/amns-2024-2011

Mots clés
SSD algorithm, SSD-M3-SFP, Behavior recognition model, Educational management model

© 2024 Ke Zhang., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Research on the Reform of Educational Management Mode in Big Data Environment

Publié en ligne: 05 août 2024

Pages: -

Reçu: 06 avr. 2024

Accepté: 03 juil. 2024

DOI: https://doi.org/10.2478/amns-2024-2011

Mots clésSSD algorithm, SSD-M3-SFP, Behavior recognition model, Educational management model

© 2024 Ke Zhang., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Mots clés
SSD algorithm, SSD-M3-SFP, Behavior recognition model, Educational management model