Emotional artificial intelligence in teacher education: a new dimension of teacher-student interaction

Abstract

The article explores the potential of Emotional Artificial Intelligence in higher teacher education. In the context of the digital transformation of education, Artificial Intelligence technologies play a crucial role in personalizing learning, enhancing teacher-student interaction, and adapting the educational process based on students’ emotional states. The study examines the fundamental principles of Emotional Artificial Intelligence, emotion recognition methods (computer vision, voice analysis, biometric technologies), and their application in educational contexts. The advantages of implementing this technology in pedagogical universities are analyzed, particularly its ability to improve feedback between students and teachers, foster a more supportive emotional learning environment, and increase student motivation. Special attention is given to the challenges of integrating Emotional Artificial Intelligence into the educational process, such as ethical concerns regarding data privacy, technological limitations, and potential resistance from educators and students. The study identifies future research directions, including improving emotion recognition algorithms, developing ethical standards for the use of emotional data, and integrating Emotional Artificial Intelligence into digital learning platforms. The findings highlight the significant potential of Emotional Artificial Intelligence in pedagogical education to create an adaptive and emotionally responsive learning environment.