SYNERGY OF MULTIMODAL PEDAGOGY AND ARTIFICIAL INTELLIGENCE: METHODOLOGICAL FOUNDATIONS FOR THE PERSONALIZATION OF EDUCATIONAL TRAJECTORIES IN HIGHER EDUCATION

Abstract

Contemporary higher education requires a transition from standardized programs to personalized educational trajectories. This article is devoted to the development of the methodological foundations for the synergy of Multimodal Pedagogy (MMP) and Artificial Intelligence (AI) as a key factor in achieving this goal. The implementation of AI makes it possible to analyze large volumes of data on a student's learning style and progress. Integration with MMP, which utilizes various perceptual channels (visual, auditory, kinesthetic), ensures the collection of multidimensional data. This is critically important, as traditional systems often fail to take into account a student's cognitive preferences, leading to reduced effectiveness. The use of AI for analyzing multimodal data allows for the dynamic adaptation of both the content and the format of the educational material, thereby avoiding cognitive overload. The paper presents a conceptual model of this synergy, which serves as a basis for creating adaptive educational platforms and next-generation intelligent textbooks. Special attention is paid to the practical aspects of applying the model to increase engagement and the quality of material assimilation. It is concluded that this integration represents a strategic direction for enhancing the effectiveness, engagement, and quality of higher education in the digital age.