Proceedings of the 2018 International Workshop on Education Reform and Social Sciences (ERSS 2018)

Analysis and Research on the Training Mode of Applied Computer Talents in Local Universities

Authors
Xiaojuan Wang, Jiamei Xue, Yue Liu, Lei Zhang, Liming Zhang
Corresponding Author
Jiamei Xue
Available Online January 2019.
DOI
10.2991/erss-18.2019.86How to use a DOI?
Keywords
Local colleges, applied computer talents, talent training model, teaching reform.
Abstract

Based on the analysis and research on the status quo of applied computer talent training mode in local colleges and universities, this paper discusses the development of talent training plan, curriculum system construction, teacher team construction and practice link setting, The application-oriented computer talent training model with the goal of capacity and comprehensive quality training and employment-oriented.

Copyright
© 2019, 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 2018 International Workshop on Education Reform and Social Sciences (ERSS 2018)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
January 2019
ISBN
978-94-6252-664-8
ISSN
2352-5398
DOI
10.2991/erss-18.2019.86How to use a DOI?
Copyright
© 2019, 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  - Xiaojuan Wang
AU  - Jiamei Xue
AU  - Yue Liu
AU  - Lei Zhang
AU  - Liming Zhang
PY  - 2019/01
DA  - 2019/01
TI  - Analysis and Research on the Training Mode of Applied Computer Talents in Local Universities
BT  - Proceedings of the 2018 International Workshop on Education Reform and Social Sciences (ERSS 2018)
PB  - Atlantis Press
SP  - 431
EP  - 434
SN  - 2352-5398
UR  - https://doi.org/10.2991/erss-18.2019.86
DO  - 10.2991/erss-18.2019.86
ID  - Wang2019/01
ER  -