Artificial Intelligent Robots for Precision Education: A Topic Modeling-Based Bibliometric Analysis

• Published in: Educational Technology ＆ Society Vol. 26; no. 1; pp. 171 - 186
• Main Authors: Chen, Xieling, Cheng, Gary, Zou, Di, Zhong, Baichang, Xie, Haoran
• Format: Journal Article
• Language: English
• Published: Palmerston North International Forum of Educational Technology ＆ Society 01.01.2023; International Forum of Educational Technology & Society, National Taiwan Normal University, Taiwan; International Forum of Educational Technology & Society
• Subjects: Artificial Intelligence; artificial intelligence robots; bibliometric analysis; Bibliometrics; Cooperative Learning; Design; Distance Education; Educational aspects; Educational Games; Educational Research; Educational Technology; future of human-centered artificial intelligence; Game Based Learning; Individualized Instruction; Interdisciplinary Approach; Learning; Learning Analytics; Learning Processes; Man Machine Systems; precision education; research topics; Robotics; Robots; Special Issue Articles; STEM Education; Technology application; Technology Uses in Education; topic modeling; China; Topic modeling; Future of human-centered artificial intelligence; Precision education; Research topics; Bibliometric analysis; Artificial intelligence robots
• ISSN: 1176-3647; 1436-4522; 1436-4522
• DOI: 10.30191/ETS.202301_26(1).0013

As a human-friendly system, the artificial intelligence (AI) robot is one of the critical applications in promoting precision education. Alongside the call for humanity-oriented applications in education, AI robot-supported precision education has developed into an active field, with increasing literature available. This study aimed to comprehensively analyze directions taken in the past in this research field to interpret a roadmap for future work. By adopting structural topic modeling, the Mann-Kendall trend test, and keyword analysis, we investigated the research topics and their dynamics in the field based on literature collected from Web of Science and Scopus databases up to 2021. Results showed that AI robots and chatbots had been widely used in different subject areas (e.g., early education, STEM education, medical, nursing, and healthcare education, and language education) for promoting collaborative learning, mobile/game-based learning, distance learning, and affective learning. However, a limited practice in developing true human-centered AI (HCAI)-supported educational robots is available. To advance HCAI in education and its application in educational robots for precision education, we suggested involving humans in AI robot design, thinking of individual learners, testing, and understanding the learner-AI robot interaction, taking an HCAI multidisciplinary approach in robot system development, and providing sufficient technical support for instructors during robot implementation.