Proceedings of the 2020 International Conference on Social Sciences and Big Data Application (ICSSBDA 2020)

Strategic Research on College English “Gold Course” Based on Production-oriented Approach

Authors
Weiwei Wang
Corresponding Author
Weiwei Wang
Available Online 2 November 2020.
DOI
10.2991/assehr.k.201030.027How to use a DOI?
Keywords
POA (Production-oriented Approach), college English, “gold course”, construction of courses
Abstract

In order to meet the assessment standards of “gold course”, it is proposed to apply the POA (Production-oriented Approach) theory into the construction of “gold course” through the implementation of the learning-centered, learning-using integration and whole-person education teaching principles with modern information technology in this paper. Through the combination of the process of motivating-enabling-assessing with the high-level, creativity and challenge of “gold course”, this paper aims to promote the organic combination and common development of the theory and the practice, so as to achieve the ultimate goal of college English “gold course” construction.

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 International Conference on Social Sciences and Big Data Application (ICSSBDA 2020)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
2 November 2020
ISBN
10.2991/assehr.k.201030.027
ISSN
2352-5398
DOI
10.2991/assehr.k.201030.027How 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  - Weiwei Wang
PY  - 2020
DA  - 2020/11/02
TI  - Strategic Research on College English “Gold Course” Based on Production-oriented Approach
BT  - Proceedings of the 2020 International Conference on Social Sciences and Big Data Application (ICSSBDA 2020)
PB  - Atlantis Press
SP  - 125
EP  - 129
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.201030.027
DO  - 10.2991/assehr.k.201030.027
ID  - Wang2020
ER  -