Proceedings of the 2020 International Conference on Advanced Education, Management and Information Technology (AEMIT 2020)

The Research on Teacher Training Strategies Based on Activation Memory

Authors
Long Zhang, Ramir S. Austria, Jie Tang
Corresponding Author
Long Zhang
Available Online 28 July 2020.
DOI
10.2991/assehr.k.200727.030How to use a DOI?
Keywords
Brain science, memory, teacher training, memory retrieval
Abstract

With the rapid development of brain and cognitive neuroscience, the research results of brain science are applied to teacher training. By inducing the long-lasting semantic memory, creating the deep episodic memory, optimizing the efficient procedural memory, stimulating the associative automatic memory and mobilizing the positive emotional memory, the memory routes are opened, and the smooth memory retrieval is realized, so as to achieve the training significance.

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 Advanced Education, Management and Information Technology (AEMIT 2020)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
28 July 2020
ISBN
10.2991/assehr.k.200727.030
ISSN
2352-5398
DOI
10.2991/assehr.k.200727.030How 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  - Long Zhang
AU  - Ramir S. Austria
AU  - Jie Tang
PY  - 2020
DA  - 2020/07/28
TI  - The Research on Teacher Training Strategies Based on Activation Memory
BT  - Proceedings of the 2020 International Conference on Advanced Education, Management and Information Technology (AEMIT 2020)
PB  - Atlantis Press
SP  - 135
EP  - 139
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.200727.030
DO  - 10.2991/assehr.k.200727.030
ID  - Zhang2020
ER  -