Proceedings of the 2021 International Conference on Social Sciences and Big Data Application (ICSSBDA 2021)

A Study of Basic Strategies and Construction of College English Listening Training on Machine

Authors
Lihua Tang
College of Foreign Language Education of China West Normal University, Nanchong, Sichuan, China
*Corresponding author. Email: 16867933@qq.com
Corresponding Author
Lihua Tang
Available Online 17 December 2021.
DOI
https://doi.org/10.2991/assehr.k.211216.010How to use a DOI?
Keywords
College English; Internet; Listening Training; Strategy
Abstract

The Internet provides convenience for college students to learn English online. At present, there are numerous strategies for English listening training, but the combination of English listening training and Internet needs to be studied more deeply and applied more widely. Built on practice, this paper explores the strategies and construction of English listening training under the network environment. It is possible to conclude that the improvement of English listening level is a long-term and gradual process, and also a process restricted by the comprehensive abilities of vocabulary, grammar, reading comprehension and knowledge.

Copyright
© 2021 The Authors. Published by Atlantis Press SARL.
Open Access
This is an open access article under the CC BY-NC license.

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Volume Title
Proceedings of the 2021 International Conference on Social Sciences and Big Data Application (ICSSBDA 2021)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
17 December 2021
ISBN
978-94-6239-487-2
ISSN
2352-5398
DOI
https://doi.org/10.2991/assehr.k.211216.010How to use a DOI?
Copyright
© 2021 The Authors. Published by Atlantis Press SARL.
Open Access
This is an open access article under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Lihua Tang
PY  - 2021
DA  - 2021/12/17
TI  - A Study of Basic Strategies and Construction of College English Listening Training on Machine
BT  - Proceedings of the 2021 International Conference on Social Sciences and Big Data Application (ICSSBDA 2021)
PB  - Atlantis Press
SP  - 49
EP  - 53
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.211216.010
DO  - https://doi.org/10.2991/assehr.k.211216.010
ID  - Tang2021
ER  -