This article examines the efficiency of digital educational platforms in mathematics teaching through the analytical modeling of interactive and electronic learning resources. The research focuses on the integration of adaptive educational technologies, artificial intelligence–based analytics, and interactive digital tools into mathematics education processes. A comprehensive digital learning environment was designed based on web and cloud technologies to support personalized learning, improve mathematical understanding, and optimize student engagement. The proposed system incorporates intelligent recommendation algorithms, real-time performance monitoring, and data-driven analytical mechanisms that dynamically adapt educational content according to students’ knowledge levels and learning behavior. Interactive mathematical simulations, electronic exercises, automated assessment modules, and visual learning resources were integrated into the platform to improve conceptual understanding and problem-solving skills. The developed analytical model evaluates students’ academic performance, learning speed, error patterns, and engagement levels using machine learning techniques and predictive analytics. Experimental studies conducted with 210 secondary school students demonstrated that the implementation of digital educational platforms increased learning effectiveness by 44%, improved mathematical problem-solving accuracy by 38%, enhanced students’ motivation by 35%, and reduced topic completion time by 31%. Furthermore, the use of interactive and electronic learning resources significantly strengthened students’ independent learning abilities and logical reasoning skills. The article is intended for educators, researchers, software engineers, and specialists working in educational technologies, digital pedagogy, and artificial intelligence in education.
Djurayeva et al. (Sat,) studied this question.