ENGLISH LANGUAGE IN SMART SCHOOLS

This article analyzes modern models for monitoring student development in smart school environments. Approaches based on digital technologies, artificial intelligence, and data analysis are considered critical tools for individualizing the educational process and enhancing its effectiveness. The study highlights the main components of monitoring systems used to assess students’ academic, social, and emotional development, their operational mechanisms, and practical applicability. Furthermore, the advantages and limitations of adaptive learning platforms, learning analytics, and real-time data collection technologies are examined through comparative analysis. Through monitoring models, the identification of individual student needs, adaptation of learning strategies, and improvement of educational quality are facilitated. The results indicate that the effective implementation of monitoring systems in smart schools optimizes teacher performance, engages students actively, and ensures transparency in the educational process. At the same time, successful implementation requires robust technical infrastructure, data security, and the development of teachers’ digital competencies. This article provides scientific and practical recommendations for enhancing monitoring systems in smart learning environments.