UDC 378:004.94

Bocharova T.A.¹ (Khabarovsk, Russian Federation) – kitaal@yandex.ru

¹Pacific State University

Abstract. The number of graduates of state universities who are employed in their specialty or in related fields is an indicator of the efficiency of spending budget funds spent on their training. The complex social system of the Russian labor market, changing under the influence of many factors, consistently demonstrates a high percentage of specialists employed in areas that do not correspond to the profile of their training. According to the Federal State Statistics Service, the professional activity of almost every third young specialist (31%) is not related to the specialty they received. The formation of professional identity of young people is influenced by their insufficient awareness of their professional interests and inclinations, the discrepancy between expectations from their future profession and reality, career guidance work aimed at identifying areas in which the future specialist has inclinations or abilities, and does not take into account his interests and hobbies, moral values. Thus, the problems of professional self-identification of Russian youth require an integrated approach to solving them. Building a model of motivational forecast for choosing a future profession, characterizing the awareness of applicants at the admission stage, using neural networks can help in establishing connections between the motivational factors for choosing a specialty and the desire to realize themselves professionally in its subject area. The article is devoted to solving the problem of typologizing the social behavior of respondents in the situation of a specific choice of a future profession. A neural network of the multilayer perceptron type with one hidden layer, trained using the backpropagation method, was used as a data processing tool. The solution is presented in the form of a visualization tool that determines (forms a forecast) based on the available answers to a number of questions, the result of a particular person belonging to a certain group with an average error value of 0.006. The proposed model can be used as an additional tool for assessing the awareness of the decision made about choosing a future profession.

Keywords: career guidance, professional self-determination, modeling, forecasting, neural networks, social forecast, employment.

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For citation: Bocharova T.A. Using neural networks to build a motivational forecast for the choice of a future profession. CITISE, 2024, no. 2, pp. 506-517.