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research-article

Student offline classroom concentration identification research based on deep learning

Published: 04 February 2023 Publication History

Abstract

During the reform of the deep teaching model, students’ deep learning quality was affected and restricted by various factors. During the offline class learning process of students, the concentration of deep learning directly affects the quality of learning. This article analyzes the study focus of students in deep learning models, conducts research on the quality of class offline learning of different students, quantifies the factors that affect students’ deep learning, and builds an analysis model for quantitative comparison. Important influence factor affecting students’ offline classroom concentration, through targeted measures, improve teaching methods and quality, optimize classroom teaching models, use various methods and measures to effectively improve learning focus, and further promote the reform of teaching models. The level of concentration of students’ learning has been steadily improved, and the model of deep learning is proposed to help the teaching model reform.

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Cited By

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  • (2024)Mapping the Deep Learning in Library: A Scientometrics Analysis of China PublicationsProceedings of the 2024 International Conference on Computer and Multimedia Technology10.1145/3675249.3675260(60-63)Online publication date: 24-May-2024

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Information

Published In

cover image Journal of Computational Methods in Sciences and Engineering
Journal of Computational Methods in Sciences and Engineering  Volume 23, Issue 1
2023
532 pages

Publisher

IOS Press

Netherlands

Publication History

Published: 04 February 2023

Author Tags

  1. Deep learning
  2. offline learning
  3. classroom concentration
  4. identification
  5. measures

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View all
  • (2024)Mapping the Deep Learning in Library: A Scientometrics Analysis of China PublicationsProceedings of the 2024 International Conference on Computer and Multimedia Technology10.1145/3675249.3675260(60-63)Online publication date: 24-May-2024

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