Opportunities of hybrid metaheuristic methods for contemporary linguistic education

Abstract

The paper explores the potential of hybrid metaheuristic optimization methods in the context of contemporary linguistic pedagogy shaped by the digitalization of education. It emphasizes the insufficiency of conventional didactic models for addressing complex educational challenges such as learning personalization, adaptive instructional pathways, automated evaluation of language skills, and optimization of teaching processes. The study highlights the growing importance of metaheuristic and hybrid algorithms in linguistic education, outlines their advantages for processing multidimensional language data, and identifies major application areas, including individualized language instruction, automated assessment, and the design of adaptive learning materials. Particular attention is given to pedagogical benefits, implementation constraints, and future prospects of hybrid metaheuristic approaches as integral elements of intelligent educational systems.