Title: Research on assessment of hybrid teaching mode in colleges stems from deep learning algorithm

Authors: Jinghui Xiu; Yingnan Ye

Addresses: School of Marxism Studies, Yantai Institute of Science and Technology, Penglai, 265600, China ' Business College, Yantai Institute of Science and Technology, Penglai, 265600, China

Abstract: The blended learning model combines traditional classroom instruction with online learning and has shown significant impact in higher education. Analysis of its effectiveness reveals a decrease in the root-mean-square deviation and the smallest mean squared error, indicating optimal training results. The network intrusion detection model has the lowest mean absolute error compared to other models. The SecRPSO-SVM model has the smallest average absolute percentage error. This innovative teaching model promotes personalised and autonomous learning, cooperative learning, and interactive communication. The use of deep learning algorithms provides new methods for educational assessment and personalised learning, positively impacting the future development of higher education.

Keywords: deep learning; mixed teaching; evaluation model; SecRPSO-SVM; principal component analysis.

DOI: 10.1504/IJCSE.2024.141336

International Journal of Computational Science and Engineering, 2024 Vol.27 No.5, pp.547 - 556

Received: 02 Dec 2022
Accepted: 18 Jul 2023
Published online: 09 Sep 2024 *

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