Leveraging social network analysis in education through social robots: A review

Abstract

In recent years, there has been a growing interest in the integration of social robots into educational settings, marking a shift in traditional teaching methodologies. This article delves into the implications of incorporating social robots in educational fields investigating particularly how their usage in such settings can be supported by recent advances in the field of Social Network Analysis (SNA). The collective findings from diverse studies underscore the multifaceted benefits of social robots in education. From personalized learning experiences and the development of tutoring skills to continuous assistance, empathic interactions, and specific case studies, social robots have showcased their potential to revolutionize education across various domains. As research in this field continues to advance, the integration of social robots in educational settings holds the promise of fostering inclusive, engaging, and effective learning environments for students of all backgrounds and abilities. Furthermore, Social Network Analysis (SNA) has gained prominence in educational research due to its ability to unveil intricate patterns of interactions among students, educators, and learning resources. The second part of this study provides a comprehensive review of the application of social network analysis in education, focusing particularly on the emerging integration of social robots in this domain. By examining recent literature, this review elucidates the potential of social robots to enhance data collection, interaction analysis, and intervention strategies within educational networks. Italso discusses challenges and future directions for leveraging social robots through social net-work analysis in educational environments.