Log in

Social robots supporting children’s learning and development: Bibliometric and visual analysis

  • Published:
Education and Information Technologies Aims and scope Submit manuscript

Abstract

The presence of social robots in children’s daily environments has steadily increased. With the advancement of artificial intelligence (AI), social robots have influenced children’s learning and development. This study innovatively utilized the Web of Science database and conducted a bibliometric analysis of 517 publications on social robots supporting children’s learning and development before September 2022. Unlike most existing reviews, this study employed a synergistic combination of two complementary visualization tools, VOSviewer and CiteSpace, to map the intellectual structure and analyze the knowledge evolution path in this emerging interdisciplinary field. Specifically, VOSviewer generated visualizations depicting collaboration networks, research hotspots, and trends based on co-occurrences. CiteSpace enabled quantitative measurements of node centrality and burstness to reveal pivotal entities and emerging topics. Combining visual map** and quantitative analysis by VOSviewer and CiteSpace allowed comprehensive landscape map** for an in-depth investigation into the development of this field. This study proposes future research directions, including children’s perceptions of social robots, social robots enhancing children’s learning, social robots supporting children’s social and emotional development, and social robots for children with special needs. The findings also inform the design and application of child-friendly social robots equipped with generative AI techniques.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (France)

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

Data Availability

The datasets analyzed during the current study are available from the corresponding author on reasonable request.

References

Download references

Acknowledgments

This work is supported by the National Education Sciences Planning Project of China: “Artificial Intelligence Empowering Children’s Learning in Digital Transformation: Effect Tracking and Practice Mechanisms”, under Grant No. BHA230141.

Author information

Authors and Affiliations

Authors

Contributions

All authors contributed to the study conception and design. The conceptualization was performed by Na Zhang and Yifang Wang. Literature research, data collection and analysis were performed by **ghan Xu and **feng Zhang. The first draft of the manuscript was written by Na Zhang and **ghan Xu, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Yifang Wang.

Ethics declarations

Competing Interests

The authors have no competing interests to declare that are relevant to the content of this article.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, N., Xu, J., Zhang, X. et al. Social robots supporting children’s learning and development: Bibliometric and visual analysis. Educ Inf Technol (2023). https://doi.org/10.1007/s10639-023-12362-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10639-023-12362-8

Keywords

Navigation