Unraveling the Dynamics of AI for Emotion in Education: A Bibliometric Perspective

This study conducted a comprehensive bibliometric analysis of AI-based emotion research in education from 2013 to 2023, reviewing 662 articles across Web of Science, ScienceDirect, and Scopus. Employing Citespace 6.2.4 for bibliometric analysis, the study aimed to map the field's development, evolution, and key themes in the context of education. It traced the research trajectory over time and identified evolving focal points in AI emotion studies specific to educational settings. The research revealed five primary developmental paths and 14 clustered themes, spanning from algorithms to applications and ethics, highlighting the interdisciplinary nature of AI emotion research in education. The study provides insights into the current status and future directions of AI emotion research in educational contexts, contributing to a deeper understanding of how AI can enhance personalized learning and educational experiences.