Investigating the relationship between the use of adaptive educational technologies and students’ academic performance in a blended learning environment

Abstract

In the context of the digitalization of education and the widespread adoption of blended learning, the need to enhance the effectiveness of the educational process through personalization is becoming increasingly relevant. Adaptive educational technologies are considered a key tool for individualizing learning; however, their impact on students’ academic performance remains insufficiently explored. The objective of the article is to provide a theoretical justification and analysis of the relationship between the use of adaptive educational technologies and students’ academic performance in a blended learning environment. Methods. The methodological framework of the study is based on systemic, structural-functional, and analytical approaches, as well as methods of generalization, comparison, and modeling. Results. In a study, a typology of adaptive educational technologies was developed based on their functional purpose, a system of indicators for evaluating students’ academic performance was established, and an algorithm for analyzing the correlation between technology use and learning effectiveness was designed. It is established that the effectiveness of adaptive technologies is determined by their ability to integrate cognitive, behavioral, and organizational parameters of the educational process, thereby personalizing learning pathways and increasing student engagement. Conclusions. The obtained results make it possible to consider adaptive educational technologies as a systemic factor in improving the quality of blended learning and provide a basis for further empirical research aimed at optimizing educational practices. It is demonstrated that their effectiveness depends on the level of integration into the educational environment and alignment with learning objectives and student characteristics. The proposed algorithm enables a comprehensive analysis of the relationships between technological solutions and academic performance, contributing to more informed managerial and pedagogical decision-making. Perspectives for further research include the empirical verification of the developed algorithm and the clarification of the impact of specific types of adaptive technologies on various student groups.