ARTIFICIAL INTELLIGENCE-BASED DIFFERENTIAL APPROACH: A PERSONALIZED LEARNING PATH FOR EVERY STUDENT

Abstract

This annotation presents an overview of the research statement titled “Artificial Intelligence-Based Differential Approach: A Personalized Learning Path for Every Student.” The study examines the integration of artificial intelligence (AI) technologies into Uzbekistan’s education system with the goal of developing personalized and adaptive learning environments that cater to the unique needs of every learner. The research aims to demonstrate how AI-driven differential approaches can improve educational quality, inclusivity, and sustainability in alignment with the nation’s digital transformation agenda.

The article highlights that global education is undergoing a paradigm shift—from traditional, teacher-centered instruction toward learner-centered, data-driven education. Within this shift, AI serves as both a pedagogical assistant and an analytical tool capable of collecting, processing, and interpreting student data in real time. AI systems can identify each learner’s strengths and weaknesses, adapt instructional content accordingly, and offer individualized feedback. Such technologies transform learning into a dynamic, self-regulated process in which every student progresses at their own pace and receives personalized guidance.

Methodologically, the research employs a mixed-method approach, combining qualitative teacher interviews with quantitative analysis of student performance data. The pilot study was conducted among secondary school students in Namangan and Tashkent regions during the 2024–2025 academic year. The integration of AI-based platforms such as ChatGPT, Duolingo, and Khan Academy showed a 32% improvement in test results and enhanced student motivation compared to traditional instruction. Teachers reported a 28% reduction in workload, as AI tools automated progress tracking and provided immediate analytics on student outcomes. These results confirm AI’s role not as a replacement for educators but as a pedagogical partner that enhances teaching efficiency and precision.

The annotation situates this research within Uzbekistan’s national policy framework, including the Presidential Decree PF–189 (October 22, 2025), Resolution PQ–320 (October 30, 2025) on supporting AI-based projects, and the “Digital Education Development Concept” (PQ–312, February 28, 2022). These documents underscore the government’s commitment to advancing AI technologies as a cornerstone of economic and educational reform. The study aligns with these policies by proposing an adaptable model of differential education that prioritizes inclusivity, accessibility, and linguistic diversity—key factors in Uzbekistan’s multilingual and multicultural educational landscape.

Furthermore, the research addresses the challenge of educational inequality between urban and rural schools. AI-supported personalization can bridge this gap by offering adaptive resources in Uzbek and Russian, supporting equitable learning opportunities nationwide. The paper ultimately argues that AI-driven differential learning is not merely a technological innovation but a strategic step toward educational modernization in Uzbekistan. By combining human expertise with intelligent systems, it envisions a future where every learner receives the support needed to reach their full potential.