Social Robots in Education: Current Trends and Future Perspectives

In contrast to other learning technologies, social robots are social and affective entities that are defined by their physical presence, their anthropomorphic characteristics, and their advanced social, emotional, and cognitive skills. Social robots are intelligent tutoring systems that can improve students’ learning, affective, and cognitive outcomes when used as tutors or peer learners offering affective and personalized learning. As the field of social robots and their use in education is rapidly advancing, this study aims to provide a review regarding the integration of social robots in education through the analysis of the existing literature to present the state of the art and to identify future research directions. Additionally, the main characteristics and properties of social robots are defined and the benefits they can bring in education are discussed. Specifically, the study examines 361 documents that derived from Scopus and the Web of Science databases. To analyze the documents, Bibliometrix, VOSviewer, topic modeling through Latent Dirichlet Allocation (LDA), and content analysis are used. An analysis of the basic characteristics of the documents (e.g., publication frequency, citation count, authors, sources, countries, affiliations, etc.) and a more in-depth analysis focusing on identifying the most prominent topics and themes as well as the thematic evolution of the topic were carried out. Finally, through the content analysis, current limitations and challenges were revealed and emerging topics and future research directions were highlighted.