Prospects and Challenges of Affective AI Technology in Supporting Remote Learning

This study analyzes the potential and challenges of introducing affective AI technologies to promote remote education. The growing popularity of remote learning highlights the significant upside of affective AI in real-time emotional monitoring and feedback, especially for improving learning motivation, optimizing personalized educational paths, and supporting students' mental health. This study explores the particular applications of affective AI technologies and the ethical and privacy concerns they present. The research indicates that affective AI technology, based on the principles of affective computing, may strengthen students' emotional management abilities, improve the overall educational experience by identifying their emotional states in real time, and create more possibilities for teacher-student interactions. Affective AI enhances student motivation and optimizes personalized learning paths in remote education, especially for fostering positive emotional regulation and mental health support outcomes. However, affective AI encounters challenge related to technical prejudice, privacy protection, ethical fairness, and user acceptance in extensive applications, particularly notable disparities in multicultural contexts, which require solutions through privacy safeguards, algorithm refinement, and culturally adaptive design. This study is significant as it systematically reveals the potential of affective AI technologies in remote learning, identifies their critical challenges, and offers valuable recommendations and references for future advancement in global education.