ACTUAL PROBLEMS AND THE LEVEL OF IMPLEMENTATION OF IOT AND MACHINE LEARNING TECHNOLOGIES IN UNIVERSITIES

Abstract

In the context of the rapid development of digital technologies, higher education systems are faced with the need to integrate advanced solutions to improve the quality of training and train competitive specialists. One such solution is the Internet of Things (IoT) and machine learning technologies, which are widely used in the educational environment. IoT integration allows universities not only to automate infrastructure, but also to create an intelligent educational space that provides a personalized approach to teaching. In turn, machine learning opens up opportunities for analyzing large educational data, adapting training courses to the individual trajectories of students and predicting their progress. Despite the obvious advantages, the introduction of these technologies in higher education is accompanied by a number of challenges: the lack of a technical base, insufficient qualifications of teachers, as well as the lack of unified strategies for digital transformation. This article discusses the current level of implementation of IoT and machine learning in universities of the Republic of Kazakhstan, analyzes the main problems and offers possible ways to solve them. In addition, the study considers the best practices for integrating these technologies in the global educational space, which makes it possible to compare the level of digitalization of domestic universities with international trends. Particular attention is paid to the pedagogical and organizational aspects of the implementation of innovative solutions. The results of the analysis can be useful for developing educational programs at universities and improving the skills of teachers. The proposed conclusions and recommendations are aimed at encouraging a more effective and systematic approach to the use of IoT and machine learning in higher education in Kazakhstan.