THE POSSIBILITIES OF INTEGRATING ARTIFICIAL INTELLIGENCE INTO THE TRADITIONAL METHODOLOGICAL SYSTEM OF TEACHING DISCRETE MATHEMATICS IN HIGHER EDUCATION INSTITUTIONS
DOI:
https://doi.org/10.32999/ksu2413-1865/2026-113-4Keywords:
discrete mathematics; methodological system; artificial intelligence; generative AI; higher education; assessment; verification of reasoning; academic integrityAbstract
Abstract. This article examines how artificial intelligence (AI) tools can be methodically integrated intoteaching discrete mathematics in higher education. The focus is on moving from isolated AI-use scenariosto a systemic approach in which AI functions are aligned with learning goals, content, teaching methods,and assessment of learning outcomes.Purpose. To substantiate the possibilities of integrating AI into the traditional methodological systemof teaching discrete mathematics in higher education by aligning AI functions with course topics, task types,usage regulations, and criteria for verifying learning outcomes.Methods. The study analyses and synthesises scholarly sources on AI integration in mathematics education,the use of intelligent tutoring systems in mathematics learning, and the application of generative AI in educationalassessment. Based on the reviewed literature, a conceptual and methodological design approach is used to developan AI integration matrix following the scheme “topic – function – task – regulation – verification”. Results. The findings show that most recent studies describe local AI-use practices, while systemic modelsthat transform the methodological system as a whole are relatively limited. The paper argues for viewingAI as a structural component of the methodological system in higher education. An AI integration matrix isproposed for key discrete mathematics topics (logic, proof methods, combinatorics, recurrences/recursion,graphs, number theory, formal languages/automata), including permissible modes of AI use and criteria forverifying reasoning. Conclusions. Systemic AI integration in teaching discrete mathematics should involvenot only the use of tools but also clear rules and verification procedures for learning outcomes. Assessment isthe most sensitive component: in discrete mathematics, priority should be given to verifying the correctnessof reasoning and proofs rather than only the final answer.