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https://doi.org/10.15405/epsbs...
Article . 2018 . Peer-reviewed
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Neuro-Technologies For Knowledge Transfer And Experience Communication

Authors: M.Yu. Ababkova*; N.N. Pokrovskaia; I.R. Trostinskaya;

Neuro-Technologies For Knowledge Transfer And Experience Communication

Abstract

The training and education systems can utilise the neuro-web and neuro-technologies for communicating and transferring knowledge and competencies and for correcting problems in the reality’ reflection, perception and understanding. The advantage of neuro-communications is built on the capacity to detect directly individuals’ perverse behaviours or attitudes, and to influence directly the emotions, feelings or sensations. The implementation of the neuro-technologies for the educational purposes permits one to adapt the process of getting and applying knowledge and skills with a higher level of individualization and concretization. Understood in this wide sense, the education or training process is similar to the socialisation, the knowledge and experience transfer concerns any situations of learning, as well everyday situations in the organisational or economic behaviour, in professional growth and in the social construction of networks of cultural activities. This paper aims to contribute to the analysis of the neuro-technologies within the knowledge transfer through the conceptual study of the potential ways of the neural networks’ implementation to exchange the skills and competences and to communicate the experience of a student towards a teacher, taking into account that in different moments any of the roles can be played by the actors. The purpose of this conceptual analysis is to structure the approaches of the neuro-communications and to configure the ethical vision of the potential, carrying out the neuro-research, in cognitive economics or in the knowledge transfer.

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    9
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
9
Top 10%
Top 10%
Top 10%
bronze