Proceedings of the International Conference on Education Innovation and Social Science (ICEISS 2017)

Research on Competition Training Based on Blended Learning

Authors
Jie Liu, Xiaoli Long
Corresponding Author
Jie Liu
Available Online November 2017.
DOI
https://doi.org/10.2991/iceiss-17.2017.5How to use a DOI?
Keywords
Blended learning; Competition training; Task driven teaching; Mobile learning
Abstract
Traditional courcing competition integration training can not change the situation of passive learning. Blended learning based on mobile learning is mainly based on students' self-study, which can realize students' personalized learning. Competition training based on blended learning is bound to change the learning state of students. A competion training mode based on blended learning is proposed, which is devided into three stages in this paper. According to task driven teaching, the training is designed with several tasks. This paper systematically discusses the theoretical basis of task driven teaching competition training based on blended learning, then describes the design and implementation. The trainning mode would make online learning more convenient and personalized, and make teaching and learning become normal, so that online and offline learning depth fused and personalized.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Proceedings
International Conference on Education Innovation and Social Science (ICEISS 2017)
Part of series
Advances in Social Science, Education and Humanities Research
Publication Date
November 2017
ISBN
978-94-6252-421-7
ISSN
2352-5398
DOI
https://doi.org/10.2991/iceiss-17.2017.5How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Jie Liu
AU  - Xiaoli Long
PY  - 2017/11
DA  - 2017/11
TI  - Research on Competition Training Based on Blended Learning
BT  - International Conference on Education Innovation and Social Science (ICEISS 2017)
PB  - Atlantis Press
SN  - 2352-5398
UR  - https://doi.org/10.2991/iceiss-17.2017.5
DO  - https://doi.org/10.2991/iceiss-17.2017.5
ID  - Liu2017/11
ER  -