UDC 378.147:004.8

Bocharova T.A.¹ (Khabarovsk, Russian Federation) – kitaal@yandex.ru; Bocharov A.V.² (St. Petersburg, Russian Federation) – artm.bocharov.06@mail.ru; Dovgal I.D.¹ (Khabarovsk, Russian Federation) – 2024102082@togudv.ru

¹Pacific State University

²Saint Petersburg State Electrotechnical University «LETI» named after V.I. Ulyanov (Lenin)

Abstract. An important factor in the success of learning, determined by external and internal incentives, is educational motivation. A comprehensive study of the mechanisms for forming a sustainable interest in learning, involvement, and desire for self-development in the educational process seems very relevant in the context of transformation and digitalization. Modern educational strategies require the integration of innovative tools to improve the efficiency of the educational process. A special place among others is occupied by generative artificial intelligence, which is a qualitatively new unique technology, a distinctive feature of which is the ability to create new content. In the educational process, generative AI has wide possibilities: from creating personalized educational materials adapted to the level of knowledge and learning style of students, supporting research activities through big data analysis, to developing language skills and increasing motivation of students through interactivity, gamification and adaptability of learning. The article is devoted to the study of issues related to the influence of generative artificial intelligence technologies on stimulating cognitive activity, as well as the formation and development of students’ educational motivation. The study includes a classification of generative AI systems by the type of generated content (text, visual and multimedia systems), by architectural features (deep generative models (GAN, VAE, transformers, diffusion models) and hybrid systems), as well as a description of their advantages: accessibility, versatility, adaptability and the ability to stimulate cognitive activity. Based on a survey among students of TPU and ETU “LETI”, the main factors influencing motivation to study due to the use of generative AI in education were identified: automation of processes, personalization of content, acceleration of development of educational materials, improvement of user experience, decision-making support. The key advantages of using the technology include time saving, round-the-clock advisory support, personalization of learning, stress reduction and development of new skills. The role of generative AI in the formation of professional competencies and intrinsic motivation of students is noted.

Keywords: generative artificial intelligence, deep generative models, hybrid systems, learning motivation, educational process.

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For citation: Bocharova T.A., Bocharov A.V., Dovgal I.D. Influence of generative artificial intelligence on students’ motivation in the educational process. CITISE, 2025, no. 3, pp. 68-80.