Keyword: «prompt engineering»

The article analyzes the advantages and disadvantages of using neural networks as part of a marketing course. Several examples of the use of artificial intelligence by students to solve marketing problems are given. The main conclusion is that the integration of neural networks into the educational process can significantly enrich student learning, improve understanding of complex topics and increase educational effectiveness, provided that the assessment system is modified.

The relevance of the study is driven by the intensive digital transformation of the education system, which reveals a systemic shortage of teaching staff capable of not only technically mastering but also methodically integrating artificial intelligence (AI) technologies into their professional practice. This problem is confirmed by the results of a diagnostic experiment, which found that 89.4% of preservice teachers have an introductory and initial level of AI competence. The aim of the research was to develop and theoretically substantiate a specialized laboratory practicum project designed to develop a holistic digital pedagogical competence in students – a complex quality combining technological skills, methodological flexibility, a reflective stance, and readiness for innovation. The methodological foundation comprised competency-based and systemic approaches, implemented through an original two-tier assignment model. The instrumental level focused on mastering basic AI tools (generative neural networks, speech recognition and synthesis platforms, dialog systems and chatbots), while the competency level focused on the pedagogical design and testing of AI solutions in simulated learning situations. The substantive content of the practicum is presented through four interconnected modules: fundamentals of prompt engineering, development of electronic educational resources using AI, application of speech technologies (ASR/TTS) for creating an inclusive environment, and design of dialog systems (chatbots) for organizing feedback and self-assessment. The main result of the study is the developed laboratory practicum project, which ensures a gradual transition from the acquisition of technical skills to the development of the capacity for pedagogical design. A key feature of the model is the mandatory reflection on each technical action, encompassing the justification of its didactic appropriateness, analysis of potential ethical risks, and design of specific scenarios for using AI in real school practice. The theoretical significance of the work lies in the development and scientific substantiation of an integrated competency model that synthesizes the technical and pedagogical aspects of preservice teacher training, thereby contributing to the advancement of pedagogical education methodology in the context of digitalization. The practical significance lies in the fact that the implementation of this practicum in the university's educational process allows students to purposefully develop not only confident digital skills but also critical soft skills: ethical reflection, methodological flexibility, and sustained readiness for innovative professional activity.