University as an analogue of the neural network

Abstract

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.