This article examines the organization of adaptive learning within a digital educational environment in higher education. It introduces N. Fleming’s VARK learning style model, which reflects the psychological characteristics of cognitive structures and students’ preferred modes of interacting with educational content. The study also considers J. Bruner’s methodology, which supports differentiated instruction based on dominant thinking styles and enables an individualized approach to analyzing and processing learning material.

Drawing on these theoretical foundations, an adaptive programming learning model was designed and implemented for students majoring in Informatics. As part of the implementation process, digital instructional modules were developed and integrated into the Khan Academy platform. In the experimental phase, students completed courses tailored to their cognitive styles, which led to an average 15% improvement in academic performance and enhanced understanding of complex subjects, including algorithms and data structures.

The findings confirm that the proposed model increases the effectiveness of the educational process and promotes deeper acquisition of programming skills by responding to individual learner needs. The study provides both theoretical and practical justification for employing digital technologies as instruments of adaptive learning, thereby contributing to the advancement of scientific and educational practices in the era of digital transformation.