PROSPECTS FOR THE USE OF DIGITAL AVATARS IN HIGHER EDUCATION INSTITUTIONS
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This article explores the emerging opportunities for the educational system presented by the introduction of digital technologies, with a particular focus on digital avatars. Given the ongoing digitalization of education, there is a need to adapt educational approaches, which necessitates new digital competencies among educators. The article highlights the need for creating innovative digital platforms that enable interactive engagement between students and teachers, facilitating the effective customization of curricula to address each student’s individual needs. Digital avatars, as intelligent agents, can significantly enhance the level of personalization of education by creating flexible learning environments tailored to each student’s style and pace. They not only support students in their learning process but also assist teachers by automating routine tasks. The integration of digital technologies into the educational process opens up new avenues for research and data analysis. Creatingdigital profiles of teachers, based on the principle of digital avatars, enables the collection and organization of substantial information about teaching activities. Analyzing this data can help identify effective teaching methods, evaluate the impact of various factors on student performance, and provide recommendations for improving the educational process. The author emphasizes the importance of developing algorithms for integrating digital technologies into higher education institutions, which will aid in the creation of digital universities of the future. Digital avatars could become a central component of these transformative processes, enhancing educational quality and its adaptability to the needs of modern society. However, the effective implementation of digital avatars in the educational process requires a comprehensive approach that encompasses not only technical integration but also a thorough analysis of pedagogical paradigms and ethical imperatives. Special attention must be given to ensuring user data confidentiality and developing algorithms that minimize the risks of algorithmic bias.
