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application of neural networks in training

Authors: V. V. Kazachonak;

application of neural networks in training

Abstract

The possibilities of neuropedagogy are analyzed for the development and implementation in educational practice of psychodiagnostic and psychocorrectional technologies that ensure the automation of the professional activity of teachers and psychologists in the modern ICT development environment. The organizational and pedagogical conditions for improving the efficiency of the learning system based on neural networks are determined: the selection and assignment of the main characteristics of the learner model and a clear formalization and construction of the ontology of the subject area. Based on the most important provisions of neuropedagogy, recommendations have been formulated to increase the effectiveness of training, including: 1) attention, 2) active interaction, 3) return by mistake and 4) consolidation (transition from a slow, conscious, effort-intensive thought process to a fast, unconscious, automatic mental work).Innovative trends in the development of modern education are considered, which, first of all, include 1) research and promotion of information and communication technologies with innovative pedagogy, 2) promotion of competencies and skills in the field of ICT for teachers and schools. To increase the effectiveness of the educational process in accordance with the provisions of neuropedagogy, it is proposed to use the capabilities of “techno-social” engineering at three levels of professional development: gaining knowledge, mastering knowledge, creating knowledge.

  • BIP!
    Impact byBIP!
    citations
    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).
    3
    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).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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Found an issue? Give us feedback
citations
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!
3
Top 10%
Average
Average
gold