Integration of artificial intelligence into learning platforms for engineering and computer graphics

Abstract

The rapid development of digital technologies in education necessitates the adaptation of the learning process to modern challenges, particularly through the integration of artificial intelligence (AI) into learning platforms. The use of AI in the educational environment enables the automation of task creation, personalization of learning, improvement of assessment methods, and enhancement of feedback between students and instructors. However, the implementation of such technologies presents several challenges, including insufficient preparedness of educators and students, limited technical infrastructure, and ethical concerns regarding data collection and processing. In this context, it is crucial to explore effective AI implementation strategies to overcome these barriers and optimize the learning process. The aim of this study is to assess the potential of AI integration into learning platforms for studying engineering and computer graphics, particularly in terms of improving learning efficiency and developing recommendations for its enhancement. Methods. To achieve this goal, the study employs methods of analyzing existing learning platforms, comparing different AI models in education, and evaluating their effectiveness. Results. The research findings demonstrate that AI integration contributes to the personalization of learning, automation of routine tasks, and better adaptation of the educational process to students’ individual needs. At the same time, key success factors for implementation have been identified, including the proper training of teaching staff, the development of technical infrastructure, and the establishment of clear ethical standards for AI use in education. The conclusions confirm that optimizing learning platforms with AI will significantly enhance the quality of education in engineering and computer graphics. The practical value of this study lies in formulating recommendations for the effective implementation of AI technologies in the learning process. Future research prospects include the development of new AI adaptation models for evolving learning needs and the creation of criteria for evaluating the effectiveness of AI integration in the educational environment.