IMPROVINGTHEMETHODOLOGYOFINDIVIDUALIZINGTHEEDUCATIONALPROCESSINHIGHEREDUCATIONBASEDONARTIFICIALINTELLIGENCE
Abstract
The rapid development of digital technologies has significantly influenced the higher education system, highlighting the need for personalized learning approaches. This article examines the improvement of the methodology for individualizing the educational process in higher education institutions based on artificial intelligence (AI) technologies. An adaptive learning model was developed by analyzing students’ individual learning characteristics, academic performance, and learning pace through AI-driven learning analytics. The proposed methodology enables the formation of personalized learning trajectories, automated assessment, and continuous feedback. The results of the experimental study demonstrate that AI-based individualized learning significantly enhances students’ academic achievement and learning motivation. The findings confirm the effectiveness and practical relevance of the proposed methodology for modern higher education.
Fields of Study & Subjects
Artificial Intelligence in Education
Intelligent Tutoring Systems and Adaptive Learning
Online Learning and Analytics
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 31 January 2026
- Document type
- Dataset