E3S Web Conf.
Volume 258, 2021Ural Environmental Science Forum “Sustainable Development of Industrial Region” (UESF-2021)
|Number of page(s)||14|
|Section||Psychology of Environmentally Responsible Behavior|
|Published online||20 May 2021|
University as an analogue of the neural network
1 V.I. Vernadsky Crimean Federal University, Simferopol, Russian Federation
2 Almaty University of Power Engineering and Telecommunications named Gumarbek Daukeyev, Almaty, Republic of Kazakhstan
3 L.N. Gumilyov Eurasian National University, Nur-Sultan, Republic of Kazakhstan
* Corresponding author: firstname.lastname@example.org
A mathematical model is proposed, which allows to estimate the number of successful university graduates based on parameters characterizing the effectiveness of vertical (lectures, seminars) and horizontal (peer education) training. It is shown that with low effectiveness of vertical learning, an effective means of improving the quality of education in general is the targeted formation of horizontal groups within which information is exchanged. It is shown that with extremely low quality of vertical learning, the behavior of the “university” system is characterized by phase transitions: with a smooth increase in the parameter characterizing the intensity of horizontal learning, there is an abrupt increase in the number of successful graduates. It has been established that with the existence of pronounced links between individual lecture courses, the “university” system becomes an analogue of a neural network.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.