Using artificial intelligence in the study of higher mathematics by students of technical specialties: educational effect
DOI:
https://doi.org/10.34185/1562-9945-5-162-2026-21Keywords:
artificial intelligence, technical specialties, digital education, AI platforms, mathematical modeling, mathematical analysis, information technologiesAbstract
This article explores the effectiveness of using artificial intelligence (AI) tools in sup-porting the training of technical students in higher mathematics. The aim of the article is to investigate and assess the impact of AI platforms on students’ academic performance, motiva-tion, and development of analytical thinking in the process of mastering complex mathemati-cal concepts. The research methodology is based on a comparative analysis of the functional capabilities of several AI platforms, including Maple, Wolfram Alpha, Julius AI, MathGPTPro, Symbolab, Maple Calculator, and GeoGebra, along with experimental evalua-tion of their effectiveness in real educational settings within technical universities.
The study was conducted through an analysis of students’ academic results and their in-teractions with AI tools. The findings show that AI platforms significantly reduce the time re-quired for routine calculations - such as solving differential equations or performing matrix operations - allowing students to focus on conceptual understanding. It was demonstrated that adaptive AI algorithms provide personalized learning paths by offering optimally chal-lenging tasks and instant feedback, which enhances both motivation and learning efficiency. Moreover, AI systems support automated theorem proving and modeling of complex systems, which fosters research skills and a deeper understanding of the interconnections between mathematical objects.
The practical value of this study lies in justifying the integration of AI technologies into the educational process of technical universities, aligning with modern trends of educational digitalization and contributing to the preparation of qualified engineers with strong analyti-cal competencies. The use of AI tools allows for the optimization of higher mathematics in-struction, improving both the quality of knowledge acquisition and the effectiveness of peda-gogical interaction. Future research prospects include the development of advanced algo-rithms for contextual analysis and explainable AI implementation in higher education.
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