Abstract
Artificial intelligence significantly influences the transformation of education, science, and society, marking a new stage in the development of technologies. Its active integration into the educational process enhances the level of interactivity and personalisation of learning. This article aimed to investigate the methodological foundations of applying artificial intelligence systems in vocational education and to experimentally test a pedagogical system for developing vocational education learners’ readiness to use artificial intelligence. Theoretical evidence supported the need to improve the methodology for implementing artificial intelligence based programmes in vocational education and outlines the potential for using the proposed methodology to enhance the training of future vocational education specialists in the context of educational transformations. The concept of “artificial intelligence” was defined, with its main characteristics and features outlined. This study presented a methodology for the successful implementation of artificial intelligence systems in the preparation of specialists in the field of vocational education. It has been identified that the promising directions for improving the implementation of educational programmes aimed at training future specialists in vocational education through the use of artificial intelligence systems include specific recommendations on the methodology of their application during the teaching of the course “Fundamentals of Artificial Intelligence”. In the context of implementing this methodology, it was recommended to use the following artificial intelligence services: SlideBot, Quizlet, DALL-E, Gemini, and ChatGPT in the teaching of the “Fundamentals of Artificial Intelligence” course within the implementation of educational and professional programmes in “Vocational education. Technology of light industry products (garments)” and “Vocational education. Transport (Car maintenance and repair)”. A pedagogical system for developing vocational education learners’ readiness to use artificial intelligence has been proposed, which includes the following stages: needs analysis and identification, development of methodological foundations, implementation and piloting, scaling and dissemination, monitoring and evaluation. The presented pedagogical system was based on three interrelated components of readiness formation: motivation-goal, cognitive-activity, and results evaluation. The effectiveness of the presented pedagogical system was assessed at three levels: high, medium, and low
Keywords
digital technologies; pedagogical system; educational transformations; readiness formation; interactive learning
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