Artificial intelligence technologies in ensuring the quality of professional training for specialists in the motor transport industry

Kushnir, Vadym (orcid.org/0000-0002-9495-2752) (2026) Artificial intelligence technologies in ensuring the quality of professional training for specialists in the motor transport industry . Publishing House of University of Technology, Katowice, Poland, pp. 157-166. ISBN 978-83-68422-17-7

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Abstract

The digital transformation of industry and transport infrastructure is reshaping the requirements for training specialists in the automotive sector. Ensuring the quality of vocational education in this field requires innovative tools that support adaptive learning, monitor skill acquisition, and improve training efficiency. Artificial intelligence (AI) technologies enhance quality assurance by enabling data-informed decision-making, personalized learning pathways, and continuous performance assessment. This study explores the potential of AI-driven solutions to improve the professional training of automotive transport specialists. Particular attention is given to intelligent learning systems, predictive analytics, automated assessment tools, and digital simulators that support the development of technical competencies and operational safety skills. AI-based monitoring allows educators to identify learning gaps, track progress in real time, and provide timely feedback, thereby increasing training effectiveness and reducing the risk of professional errors. The paper also highlights organizational and pedagogical conditions necessary for successful AI integration, including teacher digital competence, infrastructure readiness, and ethical considerations related to data protection and algorithmic transparency. The findings indicate that AI technologies contribute to improved training quality, better alignment with labor market demands, and strengthened safety-oriented professional behavior.

Item Type:	Book
Keywords:	Artificial intelligence, vocational education, automotive transport training, quality assurance, adaptive learning, predictive analytics.
Subjects:	Science and knowledge. Organization. Computer science. Information. Documentation. Librarianship. Institutions. Publications > 00 Prolegomena. Fundamentals of knowledge and culture. Propaedeutics > 004 Computer science and technology. Computing. Data processing > 004.7 Computer communication. Computer networks Science and knowledge. Organization. Computer science. Information. Documentation. Librarianship. Institutions. Publications > 00 Prolegomena. Fundamentals of knowledge and culture. Propaedeutics > 004 Computer science and technology. Computing. Data processing > 004.9 Application-oriented computer-based techniques Science and knowledge. Organization. Computer science. Information. Documentation. Librarianship. Institutions. Publications > 3 Social Sciences > 37 Education > 37.01/.09 Special auxiliary table for theory, principles, methods and organization of education Science and knowledge. Organization. Computer science. Information. Documentation. Librarianship. Institutions. Publications > 3 Social Sciences > 37 Education > 377 Specialized instruction. Vocational, technical, professional training. Vocational colleges, institutes. Polytechnics
Divisions:	Institute of Vocational Education > Department of Digital Educational Resources
Depositing User:	Ph.D. Вадим Володимирович Кушнір
Date Deposited:	11 Jun 2026 16:44
Last Modified:	11 Jun 2026 16:44
URI:	https://lib.iitta.gov.ua/id/eprint/749452

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