The study "Artificial Intelligence in Education Research during 2013–2023: A Review Based on Bibliometric Analysis" by Shuchen Guo, Yuanyuan Zheng, and Xiaoming Zhai examines the rapid advancements in Artificial Intelligence in Education (AIED) over the past decade. Using bibliometric analysis of 6,843 publications from Web of Science and Scopus, the authors identify China, the US, India, Spain, and Germany as leading research producers. The research trends focus more on higher education than K-12 education, with 15 key trends emerging, such as Educational Robots and Large Data Mining. The study highlights the primary technologies leveraged in AIED, including machine learning, decision trees, deep learning, speech recognition, and computer vision. Major implementations include educational robots, automated grading, recommender systems, learning analytics, and intelligent tutoring systems. The research is primarily conducted in seven major subject domains, with a strong emphasis on STEM and language disciplines, particularly computer science and English education. The study aims to provide a comprehensive and objective assessment of AIED research trends and gaps, using bibliometric analysis to complement traditional literature reviews.The study "Artificial Intelligence in Education Research during 2013–2023: A Review Based on Bibliometric Analysis" by Shuchen Guo, Yuanyuan Zheng, and Xiaoming Zhai examines the rapid advancements in Artificial Intelligence in Education (AIED) over the past decade. Using bibliometric analysis of 6,843 publications from Web of Science and Scopus, the authors identify China, the US, India, Spain, and Germany as leading research producers. The research trends focus more on higher education than K-12 education, with 15 key trends emerging, such as Educational Robots and Large Data Mining. The study highlights the primary technologies leveraged in AIED, including machine learning, decision trees, deep learning, speech recognition, and computer vision. Major implementations include educational robots, automated grading, recommender systems, learning analytics, and intelligent tutoring systems. The research is primarily conducted in seven major subject domains, with a strong emphasis on STEM and language disciplines, particularly computer science and English education. The study aims to provide a comprehensive and objective assessment of AIED research trends and gaps, using bibliometric analysis to complement traditional literature reviews.