Analysis of the impact of artificial intelligence integration on the functionality of mobile learning applications

Abstract

In the modern context of digital education transformation, mobile applications are of key importance as tools for organizing the educational process and providing continuous access to educational resources. At the same time, traditional approaches to their functioning are increasingly revealing limitations stemming from insufficient levels of personalization, adaptability, and analytical support for learning. The growing complexity of digital educational environments necessitates integrating innovative algorithmic technologies to support the educational process. The purpose of the article is to analyze the impact of implementing artificial intelligence on the efficiency and functional flexibility of educational mobile applications. Research methods include a comparative analysis of the functional characteristics of mobile applications, generalization of empirical data on user interaction indicators, and a conceptual modeling method for systematizing the obtained results. The results of the study showed that integrating artificial intelligence enables a transition from static to adaptive functional solutions, increases the level of personalization of educational content, automates feedback and develops analytical tools. Positive dynamics of key indicators of the effectiveness of user interaction, in particular the level of involvement, the duration of training sessions and the effectiveness of learning the material, have been established. A conceptual model of the integration of artificial intelligence is proposed, which reflects the relationship between the technological components of the system, the functional capabilities of the applications, and the educational results of the students. Conclusions. It was established that the introduction of artificial intelligence technology acts as a system-forming factor in increasing the functional efficiency of educational mobile applications and ensures the transition from static educational models to adaptively oriented solutions. The practical significance of the obtained results lies in their potential application by developers and educational institutions to enhance digital educational platforms, improve user experience quality and optimize individual educational trajectories for education seekers.