Proceedings of the 2020 5th International Conference on Modern Management and Education Technology (MMET 2020)

English Reading Teaching Based on Deep Learning

Authors
Cong Li
Corresponding Author
Cong Li
Available Online 6 November 2020.
DOI
10.2991/assehr.k.201023.143How to use a DOI?
Keywords
College English course, deep learning, critical thinking, reading teaching
Abstract

The paper demonstrates the significance of deep learning in higher education, analyzes the elements influencing the happening and effectiveness of deep learning based on the composition framework of deep learning. Among these elements, critical thinking ability is essential to trigger and assist the cultivation of deep learning. Therefore, in the teaching practice of College English course it is meaningful to rethink the purposes of classroom reading teaching and adopt the proper approaches to improve the higher cognitive competence and finally to realize the development of thinking and comprehensive competence.

Copyright
© 2020, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2020 5th International Conference on Modern Management and Education Technology (MMET 2020)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
6 November 2020
ISBN
10.2991/assehr.k.201023.143
ISSN
2352-5398
DOI
10.2991/assehr.k.201023.143How to use a DOI?
Copyright
© 2020, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Cong Li
PY  - 2020
DA  - 2020/11/06
TI  - English Reading Teaching Based on Deep Learning
BT  - Proceedings of the 2020 5th International Conference on Modern Management and Education Technology (MMET 2020)
PB  - Atlantis Press
SP  - 723
EP  - 726
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.201023.143
DO  - 10.2991/assehr.k.201023.143
ID  - Li2020
ER  -