Proceedings of the 2017 International Conference on Computational Science and Engineering (ICCSE 2017)

Evaluation on the Innovation Ability of Talent Through Extenics Evaluation Method

Authors
Lan Lan
Corresponding Author
Lan Lan
Available Online July 2017.
DOI
10.2991/iccse-17.2017.44How to use a DOI?
Keywords
The talent's Innovation Ability, Matter-element model, Extenics evaluation method
Abstract

Using literature research, expert consultation method, the paper analyzed the elements of the talent's innovation ability, and constructed the evaluation index system including innovation thinking ability, insight, self-confidence and learning ability with 4 first level indicators and 17 second level indicators. The extension evaluation method was applied to the talent's innovation ability matter element model and an example is used to verify. The results of the study indicate that the extension evaluation method can obtain the comprehensive level of innovation ability; and evaluation results can reflect talent in different dimensions of innovation ability of the advantages and disadvantages, and provide the basis for the following targeted training program.

Copyright
© 2017, 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 2017 International Conference on Computational Science and Engineering (ICCSE 2017)
Series
Advances in Computer Science Research
Publication Date
July 2017
ISBN
10.2991/iccse-17.2017.44
ISSN
2352-538X
DOI
10.2991/iccse-17.2017.44How to use a DOI?
Copyright
© 2017, 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  - Lan Lan
PY  - 2017/07
DA  - 2017/07
TI  - Evaluation on the Innovation Ability of Talent Through Extenics Evaluation Method
BT  - Proceedings of the 2017 International Conference on Computational Science and Engineering (ICCSE 2017)
PB  - Atlantis Press
SP  - 249
EP  - 256
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccse-17.2017.44
DO  - 10.2991/iccse-17.2017.44
ID  - Lan2017/07
ER  -