OPTIMIZING PRACTICAL TRAINING FOR FUTURE PILOTS BY DEVELOPING INDIVIDUALIZED EDUCATIONAL PATHWAY

Abstract

DOI: https://doi.org/10.26565/2074-8922-2026-86-10

Abstract. This article addresses the topical issue of shaping the individual educational trajectory of future pilots during their practical training at aviation higher education institutions. It is emphasized that the effectiveness of developing professional competencies in future pilots largely depends on taking into account the individual characteristics of students, their level of preparedness, professional interests, and psychophysiological characteristics. The process of individualizing education allows for these unique aspects of each student to be taken into account, which in turn contributes to more effective learning and development. Analyzing and considering the personal characteristics of students helps create a more meaningful and enriching learning environment where everyone can realize their potential and achieve excellent results.

The purpose of the article is to analyze scientific approaches to the problem of individualization of the educational process and the organization of practical training of higher education students, as well as to examine the concept of individualized learning in higher education and its application to the professional training of future pilots. The article also explores methods for ensuring the reliability and control of information, including data verification, model calibration, analysis of underlying data, and the integration of technological tools with traditional approaches in aviation training.

The study employs methods of theoretical analysis and generalization of scientific literature, as well as approaches to ensuring the reliability and control of information, including data verification, model calibration, analysis of underlying data, and the integration of artificial intelligence technologies with traditional methods in aviation training.

Conclusions of the study indicate that the proposed structural and functional model for forming an individual educational trajectory of future pilots during practical training ensures a more effective organization of the educational process. Particular attention is paid to the integration of artificial intelligence technologies, including large language models with retrieval-augmented generation (RAG), as intelligent assistants for processing large volumes of theoretical information. The implementation of the model contributes to improving the effectiveness of professional pilot training, fostering the development of professionally significant qualities, and ensuring a high level of aviation safety.