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Research on Improving Teaching Quality and Optimizing Teaching Scheme Based on Deep Learning in Chinese Literature Scene

by Yali Wang*

Shangqiu Institute of Technology, Shangqiu, 476000, China

* Corresponding Author: Yali Wang. Email: email

Journal of Quantum Computing 2022, 4(3), 165-181. https://doi.org/10.32604/jqc.2022.039795

Abstract

With the rapid development of society nowadays, this paper begins to study the teaching strategies of promoting students’ deep learning in the Chinese literature scene, and the attitudes and teaching quality of students and teachers when learning Chinese literature. The investigation and analysis show that: (1) For example, the relationship between literary scenes and characters in the famous literary work “Three Kingdoms” is analyzed. The complex character relationships in literature are important to literary scenes and learning. (2) It explains that the suggestions when writing Chinese literary scenes need to be pragmatic, pay attention to modern people’s livelihood, and the author should integrate into the literary scene to create good works. (3) The experiment in this paper investigates the depth of students’ learning of Chinese literature and their learning methods, and discovers methods that can make students learn more deeply.

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Cite This Article

APA Style
Wang, Y. (2022). Research on improving teaching quality and optimizing teaching scheme based on deep learning in chinese literature scene. Journal of Quantum Computing, 4(3), 165-181. https://doi.org/10.32604/jqc.2022.039795
Vancouver Style
Wang Y. Research on improving teaching quality and optimizing teaching scheme based on deep learning in chinese literature scene. J Quantum Comput . 2022;4(3):165-181 https://doi.org/10.32604/jqc.2022.039795
IEEE Style
Y. Wang, “Research on Improving Teaching Quality and Optimizing Teaching Scheme Based on Deep Learning in Chinese Literature Scene,” J. Quantum Comput. , vol. 4, no. 3, pp. 165-181, 2022. https://doi.org/10.32604/jqc.2022.039795



cc Copyright © 2022 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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