Application of artificial intelligence tools in analyzing the problem of increasing the motivation of age groups of students in the system of additional professional education

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Abstract

The article investigates the peculiarities of motivation of students of different age groups in the system of additional professional education (APE), with a focus on identifying individual barriers and needs of each category. The authors note that traditional methods of organizing the educational process often do not take into account the specific characteristics of adolescents, youth, adults and the elderly, which leads to a decrease in motivation and ineffective training. The aim of the article is to demonstrate how the use of modern artificial intelligence (AI) tools, in particular chatbots capable of analyzing tone, detecting the emotional state of the user and providing personalized recommendations, can be an effective means of increasing motivation and engagement of learners of all age groups. The research relies on an integrated methodological approach that includes both quantitative data obtained through questionnaires and qualitative results from interviews and practical test runs of the chatbot. This interdisciplinary approach allows building a correlation between emotional factors, information perception characteristics, and learning outcomes. The results of the study confirm that the implementation of adaptive AI solutions contributes to a more flexible and customized educational environment where emotional support, interactive tasks, and pacing adjustments take into account the unique characteristics of each age group. The authors conclude that further development of such technologies has the potential to significantly transform the system of additional professional education, making it more effective, personalized and open to innovation.

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About the authors

Tatiana E. Smolentseva

MIREA – Russian Technological University

Author for correspondence.
Email: smoltan@bk.ru
ORCID iD: 0000-0003-4810-8734
SPIN-code: 2383-6811

Dr. Sci. (Eng.); Head, Department of Applied Mathematics

Russian Federation, Moscow

Nikita A. Prikhodko

MIREA – Russian Technological University

Email: docfr10@yandex.ru
ORCID iD: 0009-0000-1166-7896
SPIN-code: 3103-7511

Department of Practical and Applied Computer Science

Russian Federation, Moscow

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2. Fig. 1. Architecture of chatbot interaction with the user

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