Applied Mathematics and Nonlinear Sciences
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Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 8, Issue 2


Published
on

October 21, 2023


Pages


DOI

Article

Deep learning algorithm-oriented blended teaching in secondary school mathematics courses in ethnic areas

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Authors

Shifang Xu Affiliation:
School of Mathematics and Statistics, Qiannan Normal University for Nationalities, Guizhou, 558000, China.
and Chunyan Pan Affiliation:
School of Mathematics and Statistics, Qiannan Normal University for Nationalities, Guizhou, 558000, China.


Abstract

To provide teaching assistance to secondary school mathematics teachers in ethnic areas and improve the teaching effectiveness of mathematics courses, a hybrid teaching model based on deep learning algorithms is proposed. Convolutional neural networks and joint probability matrix decomposition are fused to design teaching resource recommendation methods, and hybrid teaching is carried out according to three stages: before, during, and after class. The overall mean of the questionnaire for the experimental class improved from 2.39 to 3.01, and the pass rate, merit rate, and mean score of mathematics scores increased by 13.79%, 9.02%, and 15.17 points, respectively. This method enables educational technology to be effective in mathematics curriculum and improve the quality and information of mathematics education in ethnic areas.


Keywords

Deep learning algorithm, Convolutional neural network, Probability matrix decomposition, Blended instruction, Secondary school mathematics curriculum, 97B20


Citation

Xu, S. & Pan, C. (2023). Deep learning algorithm-oriented blended teaching in secondary school mathematics courses in ethnic areas. Applied Mathematics and Nonlinear Sciences, 8(2). https://doi.org/10.2478/amns.2023.2.00727

Published by: Engineering Journals

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